tandf: Communications in Statistics - Theory and Methods: Table of ContentsTable of Contents for Communications in Statistics - Theory and Methods. List of articles from both the latest and ahead of print issues.
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tandf: Communications in Statistics - Theory and Methods: Table of Contentstandfen-USCommunications in Statistics - Theory and MethodsCommunications in Statistics - Theory and Methodshttps://www.tandfonline.com/cms/asset/6156410e-fb56-4184-b7cb-68ee90d7b10a/default_cover.jpg
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Simultaneous optimization of inventory, maintenance, and quality for production systems subject to multiple mean and variance shifts
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150522?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3078-3101<br/>. <br/>Volume 53, Issue 9, 2024, Page 3078-3101<br/>. <br/>Simultaneous optimization of inventory, maintenance, and quality for production systems subject to multiple mean and variance shiftsdoi:10.1080/03610926.2022.2150522Communications in Statistics - Theory and Methods2022-12-07T05:16:08ZKonstantinos A. TasiasDepartment of Mechanical Engineering, Active Urban Planning Zone, University of Western Macedonia, Kozani, GreeceCommunications in Statistics - Theory and Methods539307831012024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150522https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150522?af=ROn weighted generalized entropy for double truncated distribution with applications
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150821?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3102-3122<br/>. <br/>Volume 53, Issue 9, 2024, Page 3102-3122<br/>. <br/>On weighted generalized entropy for double truncated distribution with applicationsdoi:10.1080/03610926.2022.2150821Communications in Statistics - Theory and Methods2022-11-30T10:17:42ZShivangi SinghChanchal KunduDepartment of Mathematical Sciences, Rajiv Gandhi Institute of Petroleum Technology, Jais, IndiaCommunications in Statistics - Theory and Methods539310231222024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150821https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150821?af=RConcentration inequality of sums of dependent subexponential random variables and application to bounds for value-at-risk
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150822?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3123-3142<br/>. <br/>Volume 53, Issue 9, 2024, Page 3123-3142<br/>. <br/>Concentration inequality of sums of dependent subexponential random variables and application to bounds for value-at-riskdoi:10.1080/03610926.2022.2150822Communications in Statistics - Theory and Methods2022-12-02T06:21:24ZYuta TanoueInstitute for Business and Finance, Waseda University, Tokyo, JapanCommunications in Statistics - Theory and Methods539312331422024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150822https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150822?af=RAsymptotic normality of the k-NN single index regression estimator for functional weak dependence data*
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150823?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3143-3168<br/>. <br/>Volume 53, Issue 9, 2024, Page 3143-3168<br/>. <br/>Asymptotic normality of the k-NN single index regression estimator for functional weak dependence data*doi:10.1080/03610926.2022.2150823Communications in Statistics - Theory and Methods2022-11-29T11:34:35ZMustapha MohammediSalim BouzebdaAli LaksaciOussama Bouanania Université Abdelhamid Ibn Badis de Mostaganem, Mostaganem, Algérieb L.S.P.S., Université Djillali Liabès de Sidi Bel Abbès, Sidi Bel Abbès, Algériec LMAC (Laboratory of Applied Mathematics of Compiègne), Université de technologie de Compiègne, Compiègne Cedex, Franced Department of Mathematics, College of Science, King Khalid University, Abha, Saudi Arabiae L.M.S.S.A., Université Dr. Moulay Tahar de Saïda, Saïda, AlgérieCommunications in Statistics - Theory and Methods539314331682024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150823https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150823?af=RAsymptotics of M-estimators for moderate deviations from a unit root model with possibly infinite variance
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150824?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3169-3186<br/>. <br/>Volume 53, Issue 9, 2024, Page 3169-3186<br/>. <br/>Asymptotics of M-estimators for moderate deviations from a unit root model with possibly infinite variancedoi:10.1080/03610926.2022.2150824Communications in Statistics - Theory and Methods2022-12-01T05:56:48ZXiaochen WangXiaolong TangYuping Songa College of Mathematics and Sciences, Shanghai Normal University, Shanghai, Chinab School of Finance and Business, Shanghai Normal University, Shanghai, ChinaCommunications in Statistics - Theory and Methods539316931862024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150824https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150824?af=RBehavior of FWER in Normal Distributions
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150826?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3211-3225<br/>. <br/>Volume 53, Issue 9, 2024, Page 3211-3225<br/>. <br/>Behavior of FWER in Normal Distributionsdoi:10.1080/03610926.2022.2150826Communications in Statistics - Theory and Methods2022-12-01T05:58:47ZMonitirtha DeyInterdisciplinary Statistical Research Unit (ISRU), Indian Statistical Institute, Kolkata, IndiaCommunications in Statistics - Theory and Methods539321132252024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150826https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150826?af=ROn the Jajte weak law of large numbers for exchangeable random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150827?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3226-3234<br/>. <br/>Volume 53, Issue 9, 2024, Page 3226-3234<br/>. <br/>On the Jajte weak law of large numbers for exchangeable random variablesdoi:10.1080/03610926.2022.2150827Communications in Statistics - Theory and Methods2022-11-30T10:16:57ZHabib NaderiMehdi JafariPrzemysław MatułaMorteza Mohammadia Department of Mathematics, University of Sistan and Baluchestan, Zahedan, Iranb Institute of Mathematics, Marie Curie-Skłodowska University, Lublin, Polandc Department of Statistics, University of Zabol, Zabol, IranCommunications in Statistics - Theory and Methods539322632342024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150827https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150827?af=RClassifying one-parameter Fréchet populations on the basis of a non-linear fixed effects model
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2151309?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3246-3258<br/>. <br/>Volume 53, Issue 9, 2024, Page 3246-3258<br/>. <br/>Classifying one-parameter Fréchet populations on the basis of a non-linear fixed effects modeldoi:10.1080/03610926.2022.2151309Communications in Statistics - Theory and Methods2023-01-02T10:53:11ZMohammad BaratniaMahdi DoostparastDepartment of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, IranCommunications in Statistics - Theory and Methods539324632582024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2151309https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2151309?af=RPairwise comparisons using ranks in block designs
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2151310?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3259-3275<br/>. <br/>Volume 53, Issue 9, 2024, Page 3259-3275<br/>. <br/>Pairwise comparisons using ranks in block designsdoi:10.1080/03610926.2022.2151310Communications in Statistics - Theory and Methods2022-12-19T06:15:26ZDennis BoosKaiyuan DuanDepartment of Statistics, North Carolina State University, Raleigh, NC, USACommunications in Statistics - Theory and Methods539325932752024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2151310https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2151310?af=RThe effect of sample size and missingness on inference with missing data
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2152287?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3292-3311<br/>. <br/>Volume 53, Issue 9, 2024, Page 3292-3311<br/>. <br/>The effect of sample size and missingness on inference with missing datadoi:10.1080/03610926.2022.2152287Communications in Statistics - Theory and Methods2022-12-09T09:57:17ZJulian MorimotoHarvard University, Cambridge, Massachusetts, USACommunications in Statistics - Theory and Methods539329233112024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2152287https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2152287?af=RAsymptotic properties of the wavelet estimator in non parametric regression model with martingale difference errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2152288?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3312-3336<br/>. <br/>Volume 53, Issue 9, 2024, Page 3312-3336<br/>. <br/>Asymptotic properties of the wavelet estimator in non parametric regression model with martingale difference errorsdoi:10.1080/03610926.2022.2152288Communications in Statistics - Theory and Methods2022-12-08T02:33:29ZXuejun WangXin DengYi Wua School of Big Data and Statistics, Anhui University, Hefei, P.R. Chinab School of Mathematics and Finance, Chuzhou University, Chuzhou, P.R. Chinac School of Big Data and Artificial Intelligence, Chizhou University, Chizhou, P.R. ChinaCommunications in Statistics - Theory and Methods539331233362024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2152288https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2152288?af=RAsymptotics for the random time ruin probability with non stationary arrivals and Brownian perturbation
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153227?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3337-3349<br/>. <br/>Volume 53, Issue 9, 2024, Page 3337-3349<br/>. <br/>Asymptotics for the random time ruin probability with non stationary arrivals and Brownian perturbationdoi:10.1080/03610926.2022.2153227Communications in Statistics - Theory and Methods2022-12-10T10:38:03ZYang LiuZhenlong ChenKe-Ang Fua School of Mathematical Sciences, Zhejiang University, Hangzhou, Chinab Department of Statistics and Data Science, Zhejiang University City College, Hangzhou, Chinac School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, ChinaCommunications in Statistics - Theory and Methods539333733492024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2153227https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153227?af=RAsymptotics in the Thurstone model with an increasing items
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153603?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3350-3364<br/>. <br/>Volume 53, Issue 9, 2024, Page 3350-3364<br/>. <br/>Asymptotics in the Thurstone model with an increasing itemsdoi:10.1080/03610926.2022.2153603Communications in Statistics - Theory and Methods2022-12-09T10:37:40ZYuyun WangJing LuoZhimeng XuLewei Zhoua Department of Statistics, Central China Normal University, Wuhan, Chinab Department of Mathematics and Statistics, South-Central MinZu University, Wuhan, ChinaCommunications in Statistics - Theory and Methods539335033642024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2153603https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153603?af=RAdaptive distributed support vector regression of massive data
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153604?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3365-3382<br/>. <br/>Volume 53, Issue 9, 2024, Page 3365-3382<br/>. <br/>Adaptive distributed support vector regression of massive datadoi:10.1080/03610926.2022.2153604Communications in Statistics - Theory and Methods2022-12-14T12:40:09ZShu-na LiangFei SunQi ZhangSchool of Mathematics and Statistics, Qingdao University, Qingdao, ChinaCommunications in Statistics - Theory and Methods539336533822024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2153604https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153604?af=RUniform-in-bandwidth consistency results in the partially linear additive model components estimation
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153605?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3383-3424<br/>. <br/>Volume 53, Issue 9, 2024, Page 3383-3424<br/>. <br/>Uniform-in-bandwidth consistency results in the partially linear additive model components estimationdoi:10.1080/03610926.2022.2153605Communications in Statistics - Theory and Methods2022-12-12T12:22:29ZKhalid ChokriSalim Bouzebdaa M.A.E.G.E. Laboratory, Hassan II University of Casablanca, Casablanca, Moroccob LMAC (Laboratory of Applied Mathematics of Compiègne), Université de technologie de Compiègne, Compiègne Cedex, FranceCommunications in Statistics - Theory and Methods539338334242024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2153605https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2153605?af=RA fortune cookie problem: A test for nominal data whether two samples are from the same population of equally likely elements
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150062?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3063-3077<br/>. <br/>Volume 53, Issue 9, 2024, Page 3063-3077<br/>. <br/>A fortune cookie problem: A test for nominal data whether two samples are from the same population of equally likely elementsdoi:10.1080/03610926.2022.2150062Communications in Statistics - Theory and Methods2022-12-01T05:54:02ZJiangtao GouKaren RuthStanley BasickesSamuel Litwina Department of Mathematics and Statistics, Villanova University, Villanova, PA, USAb Biostatistics and Bioinformatics Facility, Fox Chase Cancer Center, Philadelphia, PA, USAc Greenfield Manufacturing, Philadelphia, PA, USACommunications in Statistics - Theory and Methods539306330772024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150062https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150062?af=RExtropy properties of ranked set sample when ranking is not perfect
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150825?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3187-3210<br/>. <br/>Volume 53, Issue 9, 2024, Page 3187-3210<br/>. <br/>Extropy properties of ranked set sample when ranking is not perfectdoi:10.1080/03610926.2022.2150825Communications in Statistics - Theory and Methods2022-12-06T10:52:44ZManoj ChackoVarghese GeorgeDepartment of Statistics, University of Kerala, Trivandrum, IndiaCommunications in Statistics - Theory and Methods539318732102024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150825https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150825?af=RSupersaturated designs with less β-aberration
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150828?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3235-3245<br/>. <br/>Volume 53, Issue 9, 2024, Page 3235-3245<br/>. <br/>Supersaturated designs with less β-aberrationdoi:10.1080/03610926.2022.2150828Communications in Statistics - Theory and Methods2022-12-01T06:28:40ZUmer DarazE ChenYu TangSchool of Mathematical Sciences, Soochow University, Suzhou, ChinaCommunications in Statistics - Theory and Methods539323532452024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2150828https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2150828?af=RRegular D-optimal spring balance weighing designs with correlated errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2154128?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3425-3433<br/>. <br/>Volume 53, Issue 9, 2024, Page 3425-3433<br/>. <br/>Regular D-optimal spring balance weighing designs with correlated errorsdoi:10.1080/03610926.2022.2154128Communications in Statistics - Theory and Methods2022-12-10T10:46:13ZMałgorzata GraczykBronisław CerankaDepartment of Mathematical and Statistical Methods, Poznań University of Life Sciences, Poznań, PolandCommunications in Statistics - Theory and Methods539342534332024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2154128https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2154128?af=RDesign choices in randomization tests that affect power
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2152286?af=R
<a href="/toc/lsta20/53/9">Volume 53, Issue 9</a>, 2024, Page 3276-3291<br/>. <br/>Volume 53, Issue 9, 2024, Page 3276-3291<br/>. <br/>Design choices in randomization tests that affect powerdoi:10.1080/03610926.2022.2152286Communications in Statistics - Theory and Methods2022-12-10T10:24:07ZAbba M. KriegerDavid AzrielMichael SklarAdam Kapelnera Department of Statistics, The Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania, USAb Faculty of Industrial Engineering and Management, The Technion, Haifa, Israelc Department of Statistics, Stanford University, Stanford, California, USAd Department of Mathematics, Queens College, CUNY, New York City, New York, USACommunications in Statistics - Theory and Methods539327632912024-05-02T07:00:00Z2024-05-02T07:00:00Z10.1080/03610926.2022.2152286https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2152286?af=REstimation of complier causal treatment effects under the additive hazards model with interval-censored data
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155791?af=R
. <br/>. <br/>Estimation of complier causal treatment effects under the additive hazards model with interval-censored datadoi:10.1080/03610926.2022.2155791Communications in Statistics - Theory and Methods2022-12-14T03:25:52ZYuqing MaPeijie WangShuwei LiJianguo Suna School of Mathematics, Jilin University, Changchun, Chinab School of Economics and Statistics, Guangzhou University, Guangzhou, Chinac Department of Statistics, University of Missouri, Columbia, Missouri, USACommunications in Statistics - Theory and Methods12110.1080/03610926.2022.2155791https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155791?af=RStability of stochastic Gilpin-Ayala model driven by α-stable process under regime switching
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2154611?af=R
. <br/>. <br/>Stability of stochastic Gilpin-Ayala model driven by α-stable process under regime switchingdoi:10.1080/03610926.2022.2154611Communications in Statistics - Theory and Methods2022-12-19T06:23:40ZXuekang ZhangHuisheng ShuDajun Liua School of Mathematics-Physics and Finance, and Energy Internet Engineering Research Center of Anhui Provincial Department of Education, Anhui Polytechnic University, Wuhu, Chinab College of Science, Donghua University, Shanghai, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2022.2154611https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2154611?af=RComplete convergence and complete integral convergence for weighted sums of widely negative dependent random variables under the sub-linear expectations
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158343?af=R
. <br/>. <br/>Complete convergence and complete integral convergence for weighted sums of widely negative dependent random variables under the sub-linear expectationsdoi:10.1080/03610926.2022.2158343Communications in Statistics - Theory and Methods2022-12-19T11:02:04ZLi WangQunying WuCollege of Science, Guilin University of Technology, Guilin, PR ChinaCommunications in Statistics - Theory and Methods11710.1080/03610926.2022.2158343https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158343?af=RWeak consistency for the nonparametric kernel regression estimator based on negatively associated random errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158342?af=R
. <br/>. <br/>Weak consistency for the nonparametric kernel regression estimator based on negatively associated random errorsdoi:10.1080/03610926.2022.2158342Communications in Statistics - Theory and Methods2022-12-21T09:39:04ZLu ZhangRui WangMin WangXuejun Wanga School of Big Data and Statistics, Anhui University, Hefei, P.R. Chinab School of Mathematical Sciences, Hefei, P.R. ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2022.2158342https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158342?af=RA pseudo principal component analysis method for multi-dimensional open-high-low-close data in candlestick chart
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155787?af=R
. <br/>. <br/>A pseudo principal component analysis method for multi-dimensional open-high-low-close data in candlestick chartdoi:10.1080/03610926.2022.2155787Communications in Statistics - Theory and Methods2022-12-22T08:23:57ZWenyang HuangHuiwen WangShanshan Wanga School of Economics and Management, Beihang University, Beijing, Chinab Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing, Chinac Key Laboratory of Complex System Analysis, Management and Decision (Beihang University), Ministry of Education, Beijing, ChinaCommunications in Statistics - Theory and Methods12710.1080/03610926.2022.2155787https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155787?af=RNonparametric estimations for the cumulative distribution functions of random effects in a linear mixed-effects model
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158347?af=R
. <br/>. <br/>Nonparametric estimations for the cumulative distribution functions of random effects in a linear mixed-effects modeldoi:10.1080/03610926.2022.2158347Communications in Statistics - Theory and Methods2022-12-22T08:24:13ZLe Thi Hong ThuyCao Xuan Phuonga Faculty of Fundamental Sciences, Van Lang University, Ho Chi Minh City, Vietnamb Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, VietnamCommunications in Statistics - Theory and Methods12910.1080/03610926.2022.2158347https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158347?af=RPareto-optimal reinsurance for both the insurer and the reinsurer under the risk-adjusted value and general premium principles
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158344?af=R
. <br/>. <br/>Pareto-optimal reinsurance for both the insurer and the reinsurer under the risk-adjusted value and general premium principlesdoi:10.1080/03610926.2022.2158344Communications in Statistics - Theory and Methods2022-12-24T05:01:20ZQian BaoJiangyan PengLei ZouSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan, P.R. ChinaCommunications in Statistics - Theory and Methods12610.1080/03610926.2022.2158344https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158344?af=RLocally D-optimal designs for spline measurement error models with estimated knots
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2161823?af=R
. <br/>. <br/>Locally D-optimal designs for spline measurement error models with estimated knotsdoi:10.1080/03610926.2022.2161823Communications in Statistics - Theory and Methods2022-12-28T12:43:33ZMin-Jue ZhangRong-Xian YueXue-Ping Chena Department of Statistics, Jiangsu University of Technology, Changzhou, Chinab Department of Mathematics, Shanghai Normal University, Shanghai, ChinaCommunications in Statistics - Theory and Methods11510.1080/03610926.2022.2161823https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2161823?af=RBayesian joint modeling of binomial and rank response with non-ignorable missing data for primate cognition
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2163367?af=R
. <br/>. <br/>Bayesian joint modeling of binomial and rank response with non-ignorable missing data for primate cognitiondoi:10.1080/03610926.2022.2163367Communications in Statistics - Theory and Methods2023-01-03T09:03:51ZMaryam AghayerashtiEhsan Bahrami SamaniMojtaba GanjaliDepartment of Statistics, Faculty of Mathematical Science, Shahid Beheshti University, Tehran, IranCommunications in Statistics - Theory and Methods12110.1080/03610926.2022.2163367https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2163367?af=ROn complete moment convergence for the maximal weighted sums of NSD random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2163368?af=R
. <br/>. <br/>On complete moment convergence for the maximal weighted sums of NSD random variablesdoi:10.1080/03610926.2022.2163368Communications in Statistics - Theory and Methods2023-01-03T09:07:00ZHaiwu HuangYuan YuanWei WangHongguo Zenga School of Science, Guilin University of Aerospace Technology, Guilin, P.R. Chinab School of Big Data and Artificial Intelligence, Chizhou University, Chizhou, P.R. Chinac Library, Guilin University of Aerospace Technology, Guilin, P.R. ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2022.2163368https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2163368?af=RClassical and Bayesian estimations of performance measures in a single server Markovian queueing system based on arrivals during service times
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. <br/>. <br/>Classical and Bayesian estimations of performance measures in a single server Markovian queueing system based on arrivals during service timesdoi:10.1080/03610926.2022.2155789Communications in Statistics - Theory and Methods2023-01-03T02:01:23ZSaroja Kumar SinghFrederico R. B. CruzEriky S. GomesAbhijit Datta Banika Department of Statistics, Ravenshaw University, Cuttack, Odisha, Indiab Departamento de Estatística, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazilc School of Basic Science, Indian Institute of Technology, Bhubaneswar, Odisha, IndiaCommunications in Statistics - Theory and Methods13010.1080/03610926.2022.2155789https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155789?af=RSimultaneous population enrichment and endpoint selection in phase 3 randomized controlled trials: An adaptive group sequential design with two binary alternative primary endpoints
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. <br/>. <br/>Simultaneous population enrichment and endpoint selection in phase 3 randomized controlled trials: An adaptive group sequential design with two binary alternative primary endpointsdoi:10.1080/03610926.2022.2163180Communications in Statistics - Theory and Methods2023-01-04T05:24:44ZArup K. SinhaLemuel MoyeLinda B. PillerJose-Miguel YamalCarlos H. BarcenasJaejoon SongBarry R. Davisa Department of Biostatistics, The University of Texas School of Public Health, Houston, Texas, USAb Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, Texas, USAc Department of Breast Medical Oncology, Division of Cancer Medicine, MD Anderson Cancer Center, Houston, Texas, USAd Department of Biostatistics, MD Anderson Cancer Center, Houston, Texas, USACommunications in Statistics - Theory and Methods11410.1080/03610926.2022.2163180https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2163180?af=RComplete and complete moment convergence for arrays of rowwise asymptotically almost negatively associated random variables
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. <br/>. <br/>Complete and complete moment convergence for arrays of rowwise asymptotically almost negatively associated random variablesdoi:10.1080/03610926.2022.2164466Communications in Statistics - Theory and Methods2023-01-10T07:33:20ZAiting ShenRui Wanga School of Big Data and Statistics, Anhui University, Hefei, P.R. Chinab School of Mathematical Sciences, Anhui University, Hefei, P.R. ChinaCommunications in Statistics - Theory and Methods11510.1080/03610926.2022.2164466https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2164466?af=RGeneralized autocovariance matrices for multivariate time series
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. <br/>. <br/>Generalized autocovariance matrices for multivariate time seriesdoi:10.1080/03610926.2022.2164465Communications in Statistics - Theory and Methods2023-01-17T09:49:21ZMaddalena CavicchioliDepartment of Economics “Marco Biagi”, University of Modena and Reggio E, Modena, ItalyCommunications in Statistics - Theory and Methods12110.1080/03610926.2022.2164465https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2164465?af=RBerry-Esséen bounds and almost sure CLT for the quadratic variation of a class of Gaussian process
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. <br/>. <br/>Berry-Esséen bounds and almost sure CLT for the quadratic variation of a class of Gaussian processdoi:10.1080/03610926.2023.2167055Communications in Statistics - Theory and Methods2023-01-17T10:19:24ZYong ChenZhen DingYing Lia School of Mathematics and Statistics, Jiangxi Normal University, Nanchang, Chinab School of Mathematics and Computional Science, Xiangtan University, Xiangtan, ChinaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2167055https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2167055?af=RDoubly weighted mean score estimating functions with a partially observed effect modifier
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. <br/>. <br/>Doubly weighted mean score estimating functions with a partially observed effect modifierdoi:10.1080/03610926.2023.2166790Communications in Statistics - Theory and Methods2023-01-19T12:18:40ZMeaghan S. CuerdenLiqun DiaoCecilia A. CottonRichard J. Cooka London Health Sciences Centre, London, Canadab Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, CanadaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2166790https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2166790?af=RConsecutive Bayes factor for the mean vector
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. <br/>. <br/>Consecutive Bayes factor for the mean vectordoi:10.1080/03610926.2023.2165406Communications in Statistics - Theory and Methods2023-01-23T10:00:44ZMarzieh TaheriManouchehr KheradmandniaDepartment of Statistics, Faculty of Mathematics and Statistics, University of Isfahan, Isfahan, IranCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2165406https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2165406?af=RGeneralized location-scale mixtures of elliptical distributions: Definitions and stochastic comparisons
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. <br/>. <br/>Generalized location-scale mixtures of elliptical distributions: Definitions and stochastic comparisonsdoi:10.1080/03610926.2023.2165407Communications in Statistics - Theory and Methods2023-01-23T10:02:53ZTong PuYiying ZhangChuancun Yina Department of Mathematics, Southern University of Science and Technology, Shenzhen, Guangdong, Chinab School of Statistics and Data Science, Qufu Normal University, Qufu, Shandong, ChinaCommunications in Statistics - Theory and Methods12510.1080/03610926.2023.2165407https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2165407?af=RA bootstrap method for estimation in linear mixed models with heteroscedasticity
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. <br/>. <br/>A bootstrap method for estimation in linear mixed models with heteroscedasticitydoi:10.1080/03610926.2023.2170181Communications in Statistics - Theory and Methods2023-01-27T05:35:28ZNelum S. S. M. HapuhinnaJunfeng Shanga Department of Mathematics and Statistics, Northern Kentucky University, Highland Heights, KY, USAb Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH, USACommunications in Statistics - Theory and Methods12510.1080/03610926.2023.2170181https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2170181?af=RJoint modeling of the longitudinal student mark and the competing events of degree completion and academic dropout
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. <br/>. <br/>Joint modeling of the longitudinal student mark and the competing events of degree completion and academic dropoutdoi:10.1080/03610926.2023.2170180Communications in Statistics - Theory and Methods2023-01-28T05:32:11ZLionel Establet KemdaMichael MurraySchool of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, Durban, South AfricaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2170180https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2170180?af=RSmoothed bootstrap for right-censored data
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. <br/>. <br/>Smoothed bootstrap for right-censored datadoi:10.1080/03610926.2023.2171708Communications in Statistics - Theory and Methods2023-01-28T05:48:27ZAsamh Saleh M. Al LuhaybFrank P. A. CoolenTahani Coolen-Maturia Department of Mathematics, College of Science, Qassim University, Buraydah, Saudi Arabiab Department of Mathematical Sciences, Durham University, Durham, UKCommunications in Statistics - Theory and Methods12510.1080/03610926.2023.2171708https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2171708?af=RA measure of variability within parametric families of continuous distributions
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. <br/>. <br/>A measure of variability within parametric families of continuous distributionsdoi:10.1080/03610926.2022.2155792Communications in Statistics - Theory and Methods2023-01-11T10:47:45ZZdeněk FabiánInstitute of Computer Science, Czech Academy of Sciences, Prague, Czech RepublicCommunications in Statistics - Theory and Methods11310.1080/03610926.2022.2155792https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155792?af=RBoundary-free estimators of the mean residual life function for data on general interval
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. <br/>. <br/>Boundary-free estimators of the mean residual life function for data on general intervaldoi:10.1080/03610926.2023.2168484Communications in Statistics - Theory and Methods2023-01-30T06:28:16ZRizky Reza FauziYoshihiko Maesonoa Faculty of Information Technology and Science, Parahyangan Catholic University, Bandung, West Java, Indonesiab Faculty of Science and Engineering, Chuo University, Tokyo, JapanCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2168484https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2168484?af=ROn the hazard rate of α-mixture of survival functions
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. <br/>. <br/>On the hazard rate of α-mixture of survival functionsdoi:10.1080/03610926.2023.2172586Communications in Statistics - Theory and Methods2023-01-31T06:56:15ZOmid ShojaeeMajid AsadiMaxim Finkelsteina Department of Statistics, Faculty of Science, University of Zabol, Zabol, Sistan and Baluchestan, Iranb Department of Statistics, Faculty of Mathematics and Statistics, University of Isfahan, Isfahan, Iranc School of Mathematics, Institute for Research in Fundamental Sciences (IPM), Tehran, Irand Department of Mathematical Statistics, University of the Free State, Bloemfontein, South AfricaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2172586https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2172586?af=RMeta-analysis of exponential lifetime data from Type-I hybrid censored samples
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. <br/>. <br/>Meta-analysis of exponential lifetime data from Type-I hybrid censored samplesdoi:10.1080/03610926.2023.2169048Communications in Statistics - Theory and Methods2023-02-01T04:02:58ZKiran PrajapatShuvashree MondalSharmishtha MitraDebasis Kundua SQC & OR Unit, Indian Statistical Institute, Bengaluru, Karnataka, Indiab Department of Mathematics and Computing, Indian Institute of Technology (ISM) Dhanbad, Jharkhand, Indiac Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, IndiaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2169048https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2169048?af=RShrinkage efficiency bounds: An extension
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. <br/>. <br/>Shrinkage efficiency bounds: An extensiondoi:10.1080/03610926.2023.2173976Communications in Statistics - Theory and Methods2023-02-15T09:18:01ZGiuseppe De LucaJan R. Magnusa University of Palermo, Palermo, Italyb Vrije Universiteit Amsterdam and Tinbergen Institute, Amsterdam, The NetherlandsCommunications in Statistics - Theory and Methods1610.1080/03610926.2023.2173976https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2173976?af=RMinimum aberration 412n designs via secondary complementary sets
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2174787?af=R
. <br/>. <br/>Minimum aberration 412n designs via secondary complementary setsdoi:10.1080/03610926.2023.2174787Communications in Statistics - Theory and Methods2023-02-15T09:22:26ZYuliang ZhouShengli ZhaoQianqian ZhaoSchool of Statistics and Data Science, Qufu Normal University, Qufu, 273165 ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2174787https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2174787?af=ROn the probability of (falsely) connecting two distinct components when learning a GGM
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. <br/>. <br/>On the probability of (falsely) connecting two distinct components when learning a GGMdoi:10.1080/03610926.2023.2173973Communications in Statistics - Theory and Methods2023-02-17T10:24:55ZDaniela De CanditiisMarika Turdóa Istituto per le Applicazioni del Calcolo “M. Picone”, Rome - Italyb Università di Roma Tor Vergata, Rome - ItalyCommunications in Statistics - Theory and Methods1910.1080/03610926.2023.2173973https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2173973?af=RPrecise large deviations in a non stationary risk model with arbitrary dependence between subexponential claim sizes and waiting times
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. <br/>. <br/>Precise large deviations in a non stationary risk model with arbitrary dependence between subexponential claim sizes and waiting timesdoi:10.1080/03610926.2023.2173974Communications in Statistics - Theory and Methods2023-02-21T10:48:27ZKe-Ang FuYang LiuJiangfeng Wanga Department of Statistics and Data Science, Hangzhou City University, Hangzhou, Chinab School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, Chinac Collaborative Innovation Center of Statistical Data Engineering, Technology & Application, Zhejiang Gongshang University, Hangzhou, ChinaCommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2173974https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2173974?af=RTwo-stage conditional density estimation based on Bernstein polynomials
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. <br/>. <br/>Two-stage conditional density estimation based on Bernstein polynomialsdoi:10.1080/03610926.2023.2176715Communications in Statistics - Theory and Methods2023-02-21T11:07:42ZMohamed BelaliaGuanjie LyuDepartment of Mathematics and Statistics, University of Windsor, Ontario, CanadaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2176715https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2176715?af=RQuantile cumulative distribution function and its applications
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. <br/>. <br/>Quantile cumulative distribution function and its applicationsdoi:10.1080/03610926.2023.2176716Communications in Statistics - Theory and Methods2023-02-21T11:20:48ZAngel MathewDepartment of Statistics, Maharaja’s College, Ernakulam, Kerala, IndiaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2176716https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2176716?af=RA model calibration procedure for count response
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. <br/>. <br/>A model calibration procedure for count responsedoi:10.1080/03610926.2023.2177109Communications in Statistics - Theory and Methods2023-02-21T11:37:37ZYang SunXiangzhong FangSchool of Mathematical Sciences, Peking University, Beijing, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2177109https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2177109?af=RCopula-based multivariate EWMA control charts for monitoring the mean vector of bivariate processes using a mixture model
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. <br/>. <br/>Copula-based multivariate EWMA control charts for monitoring the mean vector of bivariate processes using a mixture modeldoi:10.1080/03610926.2023.2176717Communications in Statistics - Theory and Methods2023-02-23T08:54:07ZHussam AhmadMohammad AminiBahram Sadeghpour GildehAdel Ahmadi Nadia Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iranb Department of Statistics, Ordered Data, Reliability and Dependency Center of Excellence, Ferdowsi University of Mashhad, Mashhad, IranCommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2176717https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2176717?af=RUltrahigh dimensional single index model estimation via refitted cross-validation
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. <br/>. <br/>Ultrahigh dimensional single index model estimation via refitted cross-validationdoi:10.1080/03610926.2023.2179881Communications in Statistics - Theory and Methods2023-02-25T06:50:30ZLixia ZhangXuguang SongSchool of Statistics, Beijing Normal University, Beijing, PR ChinaCommunications in Statistics - Theory and Methods12610.1080/03610926.2023.2179881https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179881?af=RA new zero–inflated discrete Lindley regression model
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. <br/>. <br/>A new zero–inflated discrete Lindley regression modeldoi:10.1080/03610926.2023.2177108Communications in Statistics - Theory and Methods2023-02-27T11:14:28ZCaner TanışHaydar KoçAhmet Pekgöra Faculty of Science, Department of Statistics, Çankırı Karatekin University, Çankırı, Turkey;; b Faculty of Science, Department of Statistics, Necmettin Erbakan University, Çankırı, TurkeyCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2177108https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2177108?af=RMinimal circular efficient generalized strongly balanced repeated measurements designs
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. <br/>. <br/>Minimal circular efficient generalized strongly balanced repeated measurements designsdoi:10.1080/03610926.2023.2179885Communications in Statistics - Theory and Methods2023-02-27T11:45:30ZRashid AhmedM. H. TahirRida JabeenH. M. Kashif RasheedAbid KhanDepartment of Statistics, The Islamia University of Bahawalpur, Bahawalpur, PakistanCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2179885https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179885?af=RNew efficient estimators for the Weibull distribution
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. <br/>. <br/>New efficient estimators for the Weibull distributiondoi:10.1080/03610926.2023.2179880Communications in Statistics - Theory and Methods2023-02-27T11:52:15ZHyoung-Moon KimYu-Hyeong JangBarry C. ArnoldJun Zhaoa Department of Applied Statistics, Konkuk University, Seoul, Koreab Department of Statistical Science, Southern Methodist University, Dallas, Texas, USAc Department of Statistics, University of California, Riverside, California, USAd School of Mathematics and Statistics, Ningbo University, Ningbo, Zhejiang, ChinaCommunications in Statistics - Theory and Methods12610.1080/03610926.2023.2179880https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179880?af=RDesigning optimal proactive replacement strategies for degraded systems subject to two types of external shocks
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. <br/>. <br/>Designing optimal proactive replacement strategies for degraded systems subject to two types of external shocksdoi:10.1080/03610926.2023.2182179Communications in Statistics - Theory and Methods2023-02-27T12:56:30ZWenjie DongYingjie YangYingsai CaoJingru ZhangSifeng Liua College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, P.R. Chinab Institute of Artificial Intelligence, De Montfort University, The Gateway, Leicester UKc College of Management, Jiangsu University, Zhenjiang, P.R. ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2182179https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2182179?af=RSequential specification tests to choose a model: A change-point approach
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. <br/>. <br/>Sequential specification tests to choose a model: A change-point approachdoi:10.1080/03610926.2023.2179879Communications in Statistics - Theory and Methods2023-02-28T05:51:03ZAdam C SalesDepartment of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, Massachusetts, USACommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2179879https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179879?af=RResults and applications of a new inaccuracy measure based on cumulative Tsallis entropy
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. <br/>. <br/>Results and applications of a new inaccuracy measure based on cumulative Tsallis entropydoi:10.1080/03610926.2023.2179371Communications in Statistics - Theory and Methods2023-03-03T10:05:24ZDavid Chris RajuS. M. SunojG. RajeshDepartment of Statistics, Cochin University of Science and Technology, Cochin, Kerala, IndiaCommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2179371https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179371?af=RBayesian inference in a sample selection model with multiple selection rules
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. <br/>. <br/>Bayesian inference in a sample selection model with multiple selection rulesdoi:10.1080/03610926.2023.2178260Communications in Statistics - Theory and Methods2023-02-25T06:45:29ZAlireza RezaeeMojtaba GanjaliEhsan Bahrami SamaniDepartment of Statistics, Shahid Beheshti University, Tehran, IranCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2178260https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2178260?af=ROptimal dividend and stopping problems for two-dimensional compound poisson risk model
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. <br/>. <br/>Optimal dividend and stopping problems for two-dimensional compound poisson risk modeldoi:10.1080/03610926.2023.2184188Communications in Statistics - Theory and Methods2023-03-06T12:19:11ZJingwei LiGuoxin Liua Departement of Economics and Management, Tianjin Electronic Information College, Tianjin, Chinab School of Science, Hebei University of Technology, Tianjin, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2184188https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184188?af=RThe Inertial properties of EWMA control charts
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. <br/>. <br/>The Inertial properties of EWMA control chartsdoi:10.1080/03610926.2023.2184190Communications in Statistics - Theory and Methods2023-03-07T10:06:00ZPoune GhasemianRassoul Noorossanaa Industrial Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iranb Information Systems and Operations Management Department, College of Business, University of Central Oklahoma, Edmond, Oklahoma, USACommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2184190https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184190?af=RHigher-order expansions of sample range from general error distribution
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. <br/>. <br/>Higher-order expansions of sample range from general error distributiondoi:10.1080/03610926.2023.2184187Communications in Statistics - Theory and Methods2023-03-08T12:32:28ZYingyin LuXin LiaoJinhui Guoa School of Science, Southwest Petroleum University, Chengdu, Chinab School of Business, University of Shanghai for Science and Technology, Shanghai, Chinac Joint Laboratory of Data Science and Business Intelligence, Southwestern University of Finance and Economics, Chengdu, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2184187https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184187?af=RRobust equilibrium investment-reinsurance strategy for n competitive insurers with square-root factor process
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. <br/>. <br/>Robust equilibrium investment-reinsurance strategy for n competitive insurers with square-root factor processdoi:10.1080/03610926.2023.2184185Communications in Statistics - Theory and Methods2023-03-09T10:54:49ZXiaoyu XingXiaofang LiSchool of Sciences, Hebei University of Technology, Tianjin, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2184185https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184185?af=RAn extended exponential hyper-Poisson distribution: Properties and applications
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. <br/>. <br/>An extended exponential hyper-Poisson distribution: Properties and applicationsdoi:10.1080/03610926.2023.2178261Communications in Statistics - Theory and Methods2023-03-10T07:12:02ZC. Satheesh KumarA. S. SatheentharDepartment of Statistics, University of Kerala, Kariavattom, Thiruvananthapuram, IndiaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2178261https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2178261?af=RWhen are there too many collisions? Variants of the birthday problem
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. <br/>. <br/>When are there too many collisions? Variants of the birthday problemdoi:10.1080/03610926.2023.2184186Communications in Statistics - Theory and Methods2023-03-13T06:33:37ZJohn E. ConnettDivision of Biostatistics, University of Minnesota, Minneapolis, Minnesota, USACommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2184186https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184186?af=ROn a cost and availability analysis for software systems via phase type non-homogeneous Poisson process
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185473?af=R
. <br/>. <br/>On a cost and availability analysis for software systems via phase type non-homogeneous Poisson processdoi:10.1080/03610926.2023.2185473Communications in Statistics - Theory and Methods2023-03-14T09:32:25ZShenbagam R.Sarada Y.a Department of Mathematics and Actuarial Science, B.S. Abdur Rahman Crescent Institute of Science & Technology, Vandalur, Chennai, Tamil Nadu, Indiab Department of Mathematics, CEG, Anna University, Chennai, IndiaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2185473https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185473?af=RMinimally replicated PBIB designs for multi-environmental trials
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185753?af=R
. <br/>. <br/>Minimally replicated PBIB designs for multi-environmental trialsdoi:10.1080/03610926.2023.2185753Communications in Statistics - Theory and Methods2023-03-11T05:04:18ZL. N. VinaykumarCini VargheseMohd HarunSayantani Karmakara PG School, ICAR-Indian Agricultural Research Institute, PUSA, New Delhi, Indiab Division of Design of Experiments, ICAR-Indian Agricultural Statistics Research Institute, PUSA, New Delhi, IndiaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2185753https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185753?af=ROn the strong laws of large numbers for pairwise NQD random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189498?af=R
. <br/>. <br/>On the strong laws of large numbers for pairwise NQD random variablesdoi:10.1080/03610926.2023.2189498Communications in Statistics - Theory and Methods2023-03-21T06:33:22ZJianan ShiZhenhong YuYu MiaoCollege of Mathematics and Information Science, Henan Normal University, Xinxiang, Henan, ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2189498https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189498?af=RAlmost sure convergence for weighted sums of pairwise PQD random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2154129?af=R
. <br/>. <br/>Almost sure convergence for weighted sums of pairwise PQD random variablesdoi:10.1080/03610926.2022.2154129Communications in Statistics - Theory and Methods2022-12-21T09:25:09ZJoão Lita da SilvaDepartment of Mathematics and GeoBioTec, NOVA School of Science and Technology, NOVA University of Lisbon, Lisbon, PortugalCommunications in Statistics - Theory and Methods12410.1080/03610926.2022.2154129https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2154129?af=RThe failure rate for the convolution of two distributions, one of which has bounded support
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. <br/>. <br/>The failure rate for the convolution of two distributions, one of which has bounded supportdoi:10.1080/03610926.2023.2186729Communications in Statistics - Theory and Methods2023-03-22T07:25:55ZGeorge TzavelasKonstadinos PolitisDepartment of Statistics and Insurance Science, University of Piraeus, Piraeus, GreeceCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2186729https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2186729?af=RSome reliability aspects of record values using quantile functions
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189499?af=R
. <br/>. <br/>Some reliability aspects of record values using quantile functionsdoi:10.1080/03610926.2023.2189499Communications in Statistics - Theory and Methods2023-03-22T07:31:53ZI. C. AswinP. G. SankaranS. M. SunojDepartment of Statistics, Cochin University of Science and Technology, Kochi, Kerala, India 682 022.Communications in Statistics - Theory and Methods12110.1080/03610926.2023.2189499https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189499?af=RHR and RHR orderings of extremes of dependent variables under Archimedean copula
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189506?af=R
. <br/>. <br/>HR and RHR orderings of extremes of dependent variables under Archimedean copuladoi:10.1080/03610926.2023.2189506Communications in Statistics - Theory and Methods2023-03-24T06:02:20ZGhobad Saadat Kia (Barmalzan)Narayanaswamy BalakrishnanSeyed Masih AyatAbbas Akramia Department of Basic Science, Kermanshah University of Technology, Kermanshah, Iranb Department of Mathematics and Statistics, McMaster University, Hamilton, Canadac Department of Mathematics, University of Zabol, Sistan and Baluchestan, IranCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2189506https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189506?af=RStrong asymptotic properties of kernel smoothing estimation for NA random variables with right censoring
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184189?af=R
. <br/>. <br/>Strong asymptotic properties of kernel smoothing estimation for NA random variables with right censoringdoi:10.1080/03610926.2023.2184189Communications in Statistics - Theory and Methods2023-03-20T03:47:29ZJian-hua ShiJian-sen XuJin-feng Xua School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Chinab Fujian Key Laboratory of Granular Computing and Applications, Zhangzhou, Chinac The Institute of Meteorological Big Data-Digital Fujian, Zhangzhou, Chinad Fujian Key Laboratory of Data Science and Statistics, Zhangzhou, ChinaCommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2184189https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2184189?af=RComplete convergence and complete integral convergence for randomly weighted sums under the sublinear expectations
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195029?af=R
. <br/>. <br/>Complete convergence and complete integral convergence for randomly weighted sums under the sublinear expectationsdoi:10.1080/03610926.2023.2195029Communications in Statistics - Theory and Methods2023-04-03T08:48:59ZChengcheng JiaQunying WuCollege of Science, Guilin University of Technology, Guilin, P R ChinaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2195029https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195029?af=RUniform almost sure convergence rate of wavelet estimator for regression model with mixed noise
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195032?af=R
. <br/>. <br/>Uniform almost sure convergence rate of wavelet estimator for regression model with mixed noisedoi:10.1080/03610926.2023.2195032Communications in Statistics - Theory and Methods2023-04-03T08:58:56ZJunke KouQinmei HuangHao ZhangSchool of Mathematics and Computational Science, Guilin University of Electronic Technology, Guilin, Guangxi, PR ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2195032https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195032?af=RThe parameter estimations for uncertain regression model with autoregressive time series errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195034?af=R
. <br/>. <br/>The parameter estimations for uncertain regression model with autoregressive time series errorsdoi:10.1080/03610926.2023.2195034Communications in Statistics - Theory and Methods2023-04-03T09:07:13ZYuxin ShiYuhong ShengCollege of Mathematics and System Science, Xinjiang University, Urumqi, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2195034https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195034?af=RA few theoretical results for Laplace and arctan penalized ordinary least squares linear regression estimators
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195033?af=R
. <br/>. <br/>A few theoretical results for Laplace and arctan penalized ordinary least squares linear regression estimatorsdoi:10.1080/03610926.2023.2195033Communications in Statistics - Theory and Methods2023-04-04T02:14:04ZMajnu JohnSujit Vettama Departments of Mathematics and of Psychiatry, Hofstra University, Hempstead, New York, USAb Feinstein Institutes of Medical Research, Northwell Health System, Manhasset, New York, USAc The University of Chicago Booth School of Business, Chicago, Illinois, USACommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2195033https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2195033?af=RThe local limit theorem for general weighted sums of Bernoulli random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198623?af=R
. <br/>. <br/>The local limit theorem for general weighted sums of Bernoulli random variablesdoi:10.1080/03610926.2023.2198623Communications in Statistics - Theory and Methods2023-04-08T11:47:53ZPunyapat KammooKritsana NeammaneeKittipong Laipaporna Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailandb Department of Mathematics and Statistics, School of Science, Walailak University, Nakhon Si Thammarat, ThailandCommunications in Statistics - Theory and Methods1910.1080/03610926.2023.2198623https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198623?af=RShrinkage estimation in the zero-inflated Poisson regression model with right-censored data
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2196751?af=R
. <br/>. <br/>Shrinkage estimation in the zero-inflated Poisson regression model with right-censored datadoi:10.1080/03610926.2023.2196751Communications in Statistics - Theory and Methods2023-04-11T06:21:01ZZahra ZandiHossein BevraniReza Arabi BelaghiDepartment of Statistics, University of Tabriz, Tabriz, IranCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2196751https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2196751?af=RRobust consumption for individuals with pessimistic survival beliefs
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198659?af=R
. <br/>. <br/>Robust consumption for individuals with pessimistic survival beliefsdoi:10.1080/03610926.2023.2198659Communications in Statistics - Theory and Methods2023-04-12T06:28:36ZXuejiao ChenPeng LiMing ZhouBing Liua School of Economics, Minzu University of China, Beijing, Chinab School of Finance, Nanjing University of Finance and Economics, Nanjing, Chinac Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing, ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2198659https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198659?af=RPharmacokinetics with intravenous infusion of two-compartment model based on Liu process
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. <br/>. <br/>Pharmacokinetics with intravenous infusion of two-compartment model based on Liu processdoi:10.1080/03610926.2023.2198626Communications in Statistics - Theory and Methods2023-04-12T06:38:41ZZhe LiuRui Kanga School of Reliability and Systems Engineering, Beihang University, Beijing, Chinab Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, Chinac Yunnan Innovation Institute, Beihang University, Kunming, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2198626https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198626?af=REstimation and variable selection for single-index models with non ignorable missing data
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. <br/>. <br/>Estimation and variable selection for single-index models with non ignorable missing datadoi:10.1080/03610926.2023.2198625Communications in Statistics - Theory and Methods2023-04-12T07:47:02ZYue WangXiaohui YuanChunjie WangSchool of Mathematics and Statistics, Changchun University of Technology, Changchun, Jilin, ChinaCommunications in Statistics - Theory and Methods13010.1080/03610926.2023.2198625https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198625?af=RRate of convergence of discretized drift parameters estimators in the Cox–Ingersoll–Ross model
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2196591?af=R
. <br/>. <br/>Rate of convergence of discretized drift parameters estimators in the Cox–Ingersoll–Ross modeldoi:10.1080/03610926.2023.2196591Communications in Statistics - Theory and Methods2023-04-13T07:40:19ZOksana ChernovaOlena DehtiarYuliya MishuraKostiantyn RalchenkoFaculty of Mechanics and Mathematics, Taras Shevchenko National University of Kyiv, Kyiv, UkraineCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2196591https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2196591?af=RImproved estimators of hazard rate from a selected exponential population
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. <br/>. <br/>Improved estimators of hazard rate from a selected exponential populationdoi:10.1080/03610926.2023.2198624Communications in Statistics - Theory and Methods2023-04-13T09:22:50ZBrijesh Kumar JhaAjaya Kumar MahapatraSuchandan Kayala Department of Mathematics, Siksha ‘O’ Anusandhan University, Bhubaneswar, Indiab Department of Mathematics, National Institute of Technology Rourkela, Rourkela, IndiaCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2198624https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2198624?af=RA new extension of the Burr XII distribution generated by odd log-logistic random variables
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. <br/>. <br/>A new extension of the Burr XII distribution generated by odd log-logistic random variablesdoi:10.1080/03610926.2023.2200560Communications in Statistics - Theory and Methods2023-04-18T10:15:39ZMara C. T. SantosRodrigo R. Pescima Departamento de Matemática, Universidade Estadual de Londrina, Londrina, PR, Brazilb Departamento de Estatística, Universidade Estadual de Londrina, Londrina, PR, BrazilCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2200560https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2200560?af=RComplete convergence for weighted sums of widely negative dependent random variables under the sub-linear expectations
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. <br/>. <br/>Complete convergence for weighted sums of widely negative dependent random variables under the sub-linear expectationsdoi:10.1080/03610926.2023.2203283Communications in Statistics - Theory and Methods2023-04-22T04:55:45ZChengcheng JiaQunying WuCollege of Science, Guilin University of Technology, Guilin, PR ChinaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2203283https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2203283?af=RReliability modeling of weighted-k-out-of-n: G system under multiple failure modes with dependent components
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. <br/>. <br/>Reliability modeling of weighted-k-out-of-n: G system under multiple failure modes with dependent componentsdoi:10.1080/03610926.2023.2196594Communications in Statistics - Theory and Methods2023-04-22T05:29:13ZYan LiJiaqi NiuMengxue XingJinzhi Chena School of Sciences, Hebei University of Science and Technology, Shijiazhuang, Chinab School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2196594https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2196594?af=RAsymptotics of the general GEE estimator for high-dimensional longitudinal data
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. <br/>. <br/>Asymptotics of the general GEE estimator for high-dimensional longitudinal datadoi:10.1080/03610926.2023.2205045Communications in Statistics - Theory and Methods2023-04-27T05:10:12ZXianbin ChenJuliang YinSchool of Economics and Statistics, Guangzhou University, Guangzhou, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2205045https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2205045?af=RA statistical study for some classes of first-order mixed generalized binomial autoregressive models
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. <br/>. <br/>A statistical study for some classes of first-order mixed generalized binomial autoregressive modelsdoi:10.1080/03610926.2023.2205046Communications in Statistics - Theory and Methods2023-04-28T06:18:44ZJie ZhangSiyu ShaoKai YangXiaogang DongSchool of Mathematics and Statistics, Changchun University of Technology, Changchun, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2205046https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2205046?af=RDynamic risk measures via backward doubly stochastic Volterra integral equations with jumps
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. <br/>. <br/>Dynamic risk measures via backward doubly stochastic Volterra integral equations with jumpsdoi:10.1080/03610926.2023.2206503Communications in Statistics - Theory and Methods2023-04-28T06:30:18ZYanhong ChenLiangliang Miaoa College of Finance and Statistics, Hunan University, Changsha, Hunan, People’s Republic of Chinab School of Mathematical Sciences, Jiangsu Second Normal University, Nanjing, Jiangsu, People’s Republic of ChinaCommunications in Statistics - Theory and Methods12510.1080/03610926.2023.2206503https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2206503?af=RSubcritical multitype Markov branching processes with immigration generated by Poisson random measures
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2205972?af=R
. <br/>. <br/>Subcritical multitype Markov branching processes with immigration generated by Poisson random measuresdoi:10.1080/03610926.2023.2205972Communications in Statistics - Theory and Methods2023-05-05T05:41:00ZMaroussia Slavtchova-BojkovaOllivier HyrienNikolay M. Yaneva Department of PSOR, Faculty of Mathematics and Informatics, Sofia University “St. Kl. Ohridski”, Sofia, Bulgariab Department of ORPS, Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgariac Fred Hutchinson Cancer Center, Seattle, Washington, USACommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2205972https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2205972?af=RMaximum likelihood and Bayesian estimation on M/M/1 queueing model with balking
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2208695?af=R
. <br/>. <br/>Maximum likelihood and Bayesian estimation on M/M/1 queueing model with balkingdoi:10.1080/03610926.2023.2208695Communications in Statistics - Theory and Methods2023-05-09T02:38:32ZGulab Singh BuraHimanshi SharmaDepartment of Mathematics and Statistics, Banasthali Vidyapith, Rajasthan, IndiaCommunications in Statistics - Theory and Methods12910.1080/03610926.2023.2208695https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2208695?af=RThree-level saturated orthogonal arrays with less β-wordlength pattern
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2209680?af=R
. <br/>. <br/>Three-level saturated orthogonal arrays with less β-wordlength patterndoi:10.1080/03610926.2023.2209680Communications in Statistics - Theory and Methods2023-05-10T10:50:00ZJingke ZhangBeibei FanUmer DarazYu Tanga State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), Luoyang, Chinab Shanghai Bilibili Technology Co., Ltd., Shanghai, Chinac School of Mathematical Sciences, Soochow University, Suzhou, ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2209680https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2209680?af=RTochastic comparisons of series systems with heterogeneous Gompertz-G components
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. <br/>. <br/>Tochastic comparisons of series systems with heterogeneous Gompertz-G componentsdoi:10.1080/03610926.2023.2209228Communications in Statistics - Theory and Methods2023-05-11T05:19:39ZMarzieh ShekariZohreh PakdamanHossein ZamaniDepartment of Statistics, University of Hormozgan, Hormozgan, IranCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2209228https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2209228?af=RThe asymptotic distribution of a truncated sample mean for the extremely heavy-tailed distributions
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2209231?af=R
. <br/>. <br/>The asymptotic distribution of a truncated sample mean for the extremely heavy-tailed distributionsdoi:10.1080/03610926.2023.2209231Communications in Statistics - Theory and Methods2023-05-11T05:24:38ZFuquan TangDong HanDepartment of Statistics, School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2209231https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2209231?af=RReducing bias and mitigating the influence of excess of zeros in regression covariates with multi-outcome adaptive LAD-lasso
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. <br/>. <br/>Reducing bias and mitigating the influence of excess of zeros in regression covariates with multi-outcome adaptive LAD-lassodoi:10.1080/03610926.2023.2189059Communications in Statistics - Theory and Methods2023-03-23T06:26:56ZJyrki MöttönenTero LähderantaJanne SalonenMikko J. Sillanpääa Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finlandb Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finlandc Finnish Public Sector Pension Provider Keva, Helsinki, FinlandCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2189059https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2189059?af=RAn unbiased regression type estimator of proportion in randomized response sampling by using analysis of variance mechanism
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2214296?af=R
. <br/>. <br/>An unbiased regression type estimator of proportion in randomized response sampling by using analysis of variance mechanismdoi:10.1080/03610926.2023.2214296Communications in Statistics - Theory and Methods2023-05-25T09:36:18ZDaryan NaatjesStephen A. SedorySarjinder SinghDepartment of Mathematics, Texas A & M University-Kingsville, Kingsville, Texas, USACommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2214296https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2214296?af=RBayesian prior modeling in vector autoregressions via the Yule-Walker equations
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. <br/>. <br/>Bayesian prior modeling in vector autoregressions via the Yule-Walker equationsdoi:10.1080/03610926.2023.2214827Communications in Statistics - Theory and Methods2023-05-25T09:42:46ZLuigi SpeziaBiomathematics & Statistics Scotland, Aberdeen, UKCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2214827https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2214827?af=RPoisson approximation for the expectation of call function with application in collateralized debt obligation
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2215359?af=R
. <br/>. <br/>Poisson approximation for the expectation of call function with application in collateralized debt obligationdoi:10.1080/03610926.2023.2215359Communications in Statistics - Theory and Methods2023-05-25T09:55:54ZN. YonghintK. Neammaneea The Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailandb Centre of Excellence in Mathematics, Commission on Higher Education, Bangkok, ThailandCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2215359https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2215359?af=RRobust estimation strategy for handling outliers
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. <br/>. <br/>Robust estimation strategy for handling outliersdoi:10.1080/03610926.2023.2218567Communications in Statistics - Theory and Methods2023-06-06T08:09:34ZG. N. SinghD. BhattacharyyaA. Bandyopadhyaya Department of Mathematics & Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, Indiab Asansol Engineering College, Asansol, West Bengal, IndiaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2218567https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2218567?af=RObjective Bayesian analysis of Marshall-Olkin bivariate Weibull distribution with partial information
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. <br/>. <br/>Objective Bayesian analysis of Marshall-Olkin bivariate Weibull distribution with partial informationdoi:10.1080/03610926.2023.2219418Communications in Statistics - Theory and Methods2023-06-06T08:11:38ZM. S. PanwarVikas BarnwalDepartment of Statistics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, IndiaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2219418https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2219418?af=RProcess incapability index for autocorrelated data in the presence of measurement errors
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. <br/>. <br/>Process incapability index for autocorrelated data in the presence of measurement errorsdoi:10.1080/03610926.2023.2220921Communications in Statistics - Theory and Methods2023-06-12T06:06:39ZKuntal BeraM. Z. AnisSQC & OR Unit, Indian Statistical Institute, Kolkata, IndiaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2220921https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220921?af=RSequential detection of transient signal by moving likelihood ratio statistic in an exponential family
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. <br/>. <br/>Sequential detection of transient signal by moving likelihood ratio statistic in an exponential familydoi:10.1080/03610926.2023.2220922Communications in Statistics - Theory and Methods2023-06-14T04:44:45ZYanhong WuDepartment of Mathematics, California State University Stanislaus, Turlock, California, USACommunications in Statistics - Theory and Methods12610.1080/03610926.2023.2220922https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220922?af=RThe asymptotic behaviors for autoregression quantile estimates
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. <br/>. <br/>The asymptotic behaviors for autoregression quantile estimatesdoi:10.1080/03610926.2023.2221357Communications in Statistics - Theory and Methods2023-06-14T04:50:41ZXin LiMingzhi MaoGang HuangSchool of Mathematics and Physics, China University of Geosciences, Wuhan, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2221357https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2221357?af=REM estimation for the mixed Pareto regression model for claim severities
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. <br/>. <br/>EM estimation for the mixed Pareto regression model for claim severitiesdoi:10.1080/03610926.2023.2221358Communications in Statistics - Theory and Methods2023-06-14T04:54:03ZGirish AradhyeGeorge TzougasDeepesh Bhatia Department of Statistics, Central University of Rajasthan, Ajmer, Indiab Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh, UKCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2221358https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2221358?af=RAdaptive cluster sampling based on balanced sampling plan excluding contiguous units
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. <br/>. <br/>Adaptive cluster sampling based on balanced sampling plan excluding contiguous unitsdoi:10.1080/03610926.2023.2220448Communications in Statistics - Theory and Methods2023-06-20T04:46:05ZNeeraj TiwariJharna BanerjieGirish ChandraShailja Bharia Department of Statistics, S.S.J. University, Almora, Uttarakhand, Indiab Department of Statistics, D.A.V. (P.G.) College, Dehradun, Uttarakhand, Indiac Department of Statistics, University of Allahabad, Prayagraj, Uttar Pradesh, IndiaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2220448https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220448?af=RReliability analysis and optimization design of a repairable k-out-of-n retrial system with two failure modes and preventive maintenance
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. <br/>. <br/>Reliability analysis and optimization design of a repairable k-out-of-n retrial system with two failure modes and preventive maintenancedoi:10.1080/03610926.2023.2222317Communications in Statistics - Theory and Methods2023-06-20T04:46:14ZJing LiLinmin HuYuyu WangJia Kanga School of Science, Yanshan University, Qinhuangdao, Hebei, Chinab College of Mathematical Science, Tianjin Normal University, Tianjin, ChinaCommunications in Statistics - Theory and Methods12910.1080/03610926.2023.2222317https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2222317?af=RDispersion indices based on Kerridge inaccuracy measure and Kullback-Leibler divergence
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. <br/>. <br/>Dispersion indices based on Kerridge inaccuracy measure and Kullback-Leibler divergencedoi:10.1080/03610926.2023.2222926Communications in Statistics - Theory and Methods2023-06-20T04:46:34ZNarayanaswamy BalakrishnanFrancesco BuonoCamilla CalìMaria Longobardia McMaster University, Hamilton, Ontario, Canadab Dipartimento di Matematica e Applicazioni “Renato Caccioppoli,” Università degli Studi di Napoli Federico II, Naples, Italyc Institute of Statistics, RWTH Aachen University, Aachen, Germanyd Dipartimento di Biologia, Università degli Studi di Napoli Federico II, Naples, ItalyCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2222926https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2222926?af=ROn some non parametric estimators of the quantile density function for a stationary associated process
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. <br/>. <br/>On some non parametric estimators of the quantile density function for a stationary associated processdoi:10.1080/03610926.2023.2222922Communications in Statistics - Theory and Methods2023-06-21T08:01:23ZYogendra P. ChaubeyIsha DewanJun Lia Department of Mathematics and Statistics, Concordia University, Montreal, Canadab Stat Math Unit, Indian Statistical Institute, New Delhi, Delhi, Indiac School of Statistics and Mathematics, Nanjing Audit University, Nanjing, P.R. ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2222922https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2222922?af=RPositive definite functions, stationary covariance functions, and Bochner’s theorem: Some results and a critical overview
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. <br/>. <br/>Positive definite functions, stationary covariance functions, and Bochner’s theorem: Some results and a critical overviewdoi:10.1080/03610926.2023.2223780Communications in Statistics - Theory and Methods2023-06-21T02:15:17ZDonato PosaDipartimento di Scienze Economiche e Matematico-Statistiche, University of Salento, Lecce, ItalyCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2223780https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2223780?af=RRobust estimation with exponential squared loss for partially linear panel data model with fixed effects
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. <br/>. <br/>Robust estimation with exponential squared loss for partially linear panel data model with fixed effectsdoi:10.1080/03610926.2023.2226274Communications in Statistics - Theory and Methods2023-06-28T05:35:59ZPing HeYiping YangPeixin Zhaoa School of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, Chinab Chongqing Key Laboratory of Social Economic and Applied Statistics, Chongqing, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2226274https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2226274?af=RRevisit optimal reinsurance under a new distortion risk measure
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2226783?af=R
. <br/>. <br/>Revisit optimal reinsurance under a new distortion risk measuredoi:10.1080/03610926.2023.2226783Communications in Statistics - Theory and Methods2023-06-28T05:43:44ZZichao XiaWanwan XiaZhenfeng Zoua Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui, Chinab School of Physical and Mathematical Sciences, Nanjing Tech University, Nanjing, Jiangsu, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2226783https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2226783?af=RA Statistical Approach to Broken Stick Problems
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. <br/>. <br/>A Statistical Approach to Broken Stick Problemsdoi:10.1080/03610926.2023.2224909Communications in Statistics - Theory and Methods2023-06-29T06:16:11ZRahul MukerjeeIndian Institute of Management Calcutta, Joka, Diamond Harbour Road, Kolkata 700 104, IndiaCommunications in Statistics - Theory and Methods11010.1080/03610926.2023.2224909https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2224909?af=RApplying machine learning techniques in survival analysis to the private pension system in Turkey
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. <br/>. <br/>Applying machine learning techniques in survival analysis to the private pension system in Turkeydoi:10.1080/03610926.2023.2230329Communications in Statistics - Theory and Methods2023-07-06T07:12:53ZGüven ŞimşekDuru Karasoya Department of Actuarial Sciences, Faculty of Science, Hacettepe University, Ankara, Turkeyb Department of Statistics, Faculty of Science, Hacettepe University, Ankara, TurkeyCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2230329https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2230329?af=RD- and A-optimal designs for multi-response mixture experiments with qualitative factors
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. <br/>. <br/>D- and A-optimal designs for multi-response mixture experiments with qualitative factorsdoi:10.1080/03610926.2023.2223705Communications in Statistics - Theory and Methods2023-06-30T04:49:37ZJiali ChenLing LingChongqi Zhanga School of Economics and Statistics, Guangzhou University, Guangzhou, Chinab School of Mathematics and Data Science, Zhongkai University of Agriculture and Engineering, Guangzhou, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2223705https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2223705?af=RHow many times until a coincidence becomes a pattern? The case of yield curve inversions preceding recessions and the magical number 7
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. <br/>. <br/>How many times until a coincidence becomes a pattern? The case of yield curve inversions preceding recessions and the magical number 7doi:10.1080/03610926.2023.2232908Communications in Statistics - Theory and Methods2023-07-13T06:27:33ZNed KockAugustine Tarkoma Division of International Business and Technology Studies, Texas A&M International University, Laredo, Texas, USAb Division of International Banking and Finance Studies, Texas A&M International University, Laredo, Texas, USACommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2232908https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2232908?af=RA Bernstein polynomial approach to the estimation of a distribution function and quantiles under censorship model
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. <br/>. <br/>A Bernstein polynomial approach to the estimation of a distribution function and quantiles under censorship modeldoi:10.1080/03610926.2023.2228948Communications in Statistics - Theory and Methods2023-07-15T06:02:38ZSalah KhardaniFaculté des Sciences Tunis, Université El-Manar, Laboratoire de Modélisation Mathématique, Statistique et Analyse Stochastique, Tunis, TunisiaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2228948https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2228948?af=RBayesian inference using least median of squares and least trimmed squares in models with independent or correlated errors and outliers
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. <br/>. <br/>Bayesian inference using least median of squares and least trimmed squares in models with independent or correlated errors and outliersdoi:10.1080/03610926.2023.2232905Communications in Statistics - Theory and Methods2023-07-17T04:18:30ZMike TsionasLancaster University Management School, Lancaster, UKCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2232905https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2232905?af=RDetermining seasonal unit roots with bridge estimator: Monte Carlo evidence and an application to convergence hypothesis
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2231111?af=R
. <br/>. <br/>Determining seasonal unit roots with bridge estimator: Monte Carlo evidence and an application to convergence hypothesisdoi:10.1080/03610926.2023.2231111Communications in Statistics - Theory and Methods2023-07-17T04:18:05ZCigdem Kosar TasHüseyin GulerDepartment of Econometrics, Cukurova University, Adana, TurkeyCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2231111https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2231111?af=ROn the Conway-Maxwell-Poisson point process
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. <br/>. <br/>On the Conway-Maxwell-Poisson point processdoi:10.1080/03610926.2023.2229028Communications in Statistics - Theory and Methods2023-07-20T12:27:33ZIan FlintYan WangAihua Xiaa School of Agriculture, Food and Ecosystem Science, The University of Melbourne, Parkville, Victoria, Australiab School of Science, RMIT University, Melbourne VIC, Australiac School of Mathematics and Statistics, The University of Melbourne, Parkville Victoria, AustraliaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2229028https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2229028?af=RDesign of Hotelling T2 control chart using various covariance structures
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. <br/>. <br/>Design of Hotelling T2 control chart using various covariance structuresdoi:10.1080/03610926.2023.2234520Communications in Statistics - Theory and Methods2023-07-20T12:39:46ZHafiza NidaMuhammad KashifMuhammad Imran KhanLiaquat AhmadMuhammad Aslama Department of Mathematics and Statistics, University of Agriculture, Faisalabad, Pakistanb Department of Statistics and Computer Science, University of Veterinary and Animal Sciences, Lahore, Pakistanc Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi ArabiaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2234520https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2234520?af=RAn optimal screening policy for heterogeneous items with minimal repairs
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. <br/>. <br/>An optimal screening policy for heterogeneous items with minimal repairsdoi:10.1080/03610926.2023.2233150Communications in Statistics - Theory and Methods2023-07-21T06:42:27ZXiaoliang LingMeng WangYinzhao Weia College of Sciences, Hebei University of Science and Technology, Shijiazhuang, China; b School of Mathematics and Statistics, Xidian University, Xi’an, ChinaCommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2233150https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2233150?af=RNon parametric estimation of transition density for second-order diffusion processes
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. <br/>. <br/>Non parametric estimation of transition density for second-order diffusion processesdoi:10.1080/03610926.2023.2234521Communications in Statistics - Theory and Methods2023-07-21T07:30:21ZYue LiYunyan WangMingtian TangSchool of Science, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, P. R. ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2234521https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2234521?af=RReal natural exponential families and generalized orthogonality
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. <br/>. <br/>Real natural exponential families and generalized orthogonalitydoi:10.1080/03610926.2023.2235447Communications in Statistics - Theory and Methods2023-07-21T08:17:09ZRaouf FakhfakhMarwa Hamzaa College of Science and Arts in Gurayat, Jouf University, Gurayat, Saudi Arabiab Laboratory of Probability and Statistics, Faculty of Sciences of Sfax, University of Sfax, Sfax, TunisiaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2235447https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2235447?af=RAsymptotic ruin probabilities for a two-dimensional risk model with dependent claims and stochastic return
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. <br/>. <br/>Asymptotic ruin probabilities for a two-dimensional risk model with dependent claims and stochastic returndoi:10.1080/03610926.2023.2232906Communications in Statistics - Theory and Methods2023-07-21T12:41:42ZJinzhu LiSchool of Mathematical Science and LPMC Nankai University, Tianjin, P.R. ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2232906https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2232906?af=RSolvability of one kind of forward-backward stochastic difference equations
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. <br/>. <br/>Solvability of one kind of forward-backward stochastic difference equationsdoi:10.1080/03610926.2023.2235444Communications in Statistics - Theory and Methods2023-07-22T09:40:12ZShaolin JiHaodong Liua Zhongtai Securities Institute for Financial Studies, Shandong, University, Jinan, Shandong, PR Chinab School of Economics, Ocean University of China, Qingdao, Shandong, PR ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2235444https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2235444?af=RDynamic cumulative residual entropy generating function and its properties
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. <br/>. <br/>Dynamic cumulative residual entropy generating function and its propertiesdoi:10.1080/03610926.2023.2235448Communications in Statistics - Theory and Methods2023-07-24T09:42:15ZS. SmithaSudheesh K. KattumannilE.P. Sreedevia K E College Mannanam, Kerala, Indiab Indian Statistical Institute, Chennai, Indiac Cochin University of Sceince and Technology, Kochi, IndiaCommunications in Statistics - Theory and Methods12610.1080/03610926.2023.2235448https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2235448?af=RComputation of VaR for portfolios in intensity models
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. <br/>. <br/>Computation of VaR for portfolios in intensity modelsdoi:10.1080/03610926.2023.2237221Communications in Statistics - Theory and Methods2023-07-25T03:38:06ZShiyu SongYing Lua School of Mathematics and Information Science, Weifang University, Weifang, People’s Republic of Chinab Shenzhen Huaixin Enterprise Investment Consulting Co, Ltd, Shenzhen, People’s Republic of ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2237221https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2237221?af=RWeighted least squares: A robust method of estimation for sinusoidal model
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. <br/>. <br/>Weighted least squares: A robust method of estimation for sinusoidal modeldoi:10.1080/03610926.2023.2238362Communications in Statistics - Theory and Methods2023-07-30T04:18:26ZDebasis KunduDepartment of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, IndiaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2238362https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2238362?af=ROptimal confounding measures for two-level regular designs
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. <br/>. <br/>Optimal confounding measures for two-level regular designsdoi:10.1080/03610926.2023.2238859Communications in Statistics - Theory and Methods2023-07-30T04:43:28ZPeng CanZhi-Ming LiLi ZhiCollege of Mathematics and System Science, Xinjiang University, Urumqi, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2238859https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2238859?af=RA novel residual subsampling method for skew-normal mode regression model with massive data
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. <br/>. <br/>A novel residual subsampling method for skew-normal mode regression model with massive datadoi:10.1080/03610926.2023.2238860Communications in Statistics - Theory and Methods2023-08-01T05:13:47ZZhe JiangYan WuMin WangLiucang Wua Faculty of Science, Kunming University of Science and Technology, Kunming, Yunnan, Chinab Center for Applied Statistics, Kunming University of Science and Technology, Kunming, Yunnan, Chinac School of Mathematics and Statistics, Yunnan University, Kunming, Yunnan, Chinad Department of Management Science and Statistics, The University of Texas at San Antonio San Antonio, Texas, USACommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2238860https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2238860?af=RCumulative α-Jensen–Shannon measure of divergence: Properties and applications
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. <br/>. <br/>Cumulative α-Jensen–Shannon measure of divergence: Properties and applicationsdoi:10.1080/03610926.2023.2238861Communications in Statistics - Theory and Methods2023-08-02T09:42:46ZH. RiyahiM. BaratniaM. DoostparastDepartment of Statistics, Ferdowsi University of Mashhad, Mashhad, IranCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2238861https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2238861?af=RFurther results on laws of large numbers for the array of random variables under sub-linear expectation
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. <br/>. <br/>Further results on laws of large numbers for the array of random variables under sub-linear expectationdoi:10.1080/03610926.2023.2239400Communications in Statistics - Theory and Methods2023-08-02T10:28:20ZFeng HuYanan FuMiaomiao GaoZhaojun Zonga School of Statistics and Data Science, Qufu Normal University, Qufu, Chinab Department of Mathematics, Jining University, SQufu, ChinaCommunications in Statistics - Theory and Methods12610.1080/03610926.2023.2239400https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239400?af=RA new method of testing mutual independence
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239402?af=R
. <br/>. <br/>A new method of testing mutual independencedoi:10.1080/03610926.2023.2239402Communications in Statistics - Theory and Methods2023-08-03T08:46:21ZXiangyu GuoFukang ZhuSchool of Mathematics, Jilin University, Changchun, ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2239402https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239402?af=RNonparametric estimation of trend for SDEs driven by a Gaussian process
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. <br/>. <br/>Nonparametric estimation of trend for SDEs driven by a Gaussian processdoi:10.1080/03610926.2023.2240917Communications in Statistics - Theory and Methods2023-08-03T09:18:52ZB.L.S. Prakasa RaoCR RAO Advanced Institute of Mathematics, Statistics and Computer Science, Hyderabad, IndiaCommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2240917https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2240917?af=RSome asymptotic inferential aspects of the Kumaraswamy distribution
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. <br/>. <br/>Some asymptotic inferential aspects of the Kumaraswamy distributiondoi:10.1080/03610926.2023.2241091Communications in Statistics - Theory and Methods2023-08-03T09:22:51ZHérica P. A. CarneiroMônica C. SandovalDenise A. BotterTiago M. Magalhãesa Department of Statistics, University of São Paulo, São Paulo, Brazilb Department of Statistics, Federal University of Juiz de Fora, Juiz de Fora, BrazilCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2241091https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2241091?af=RWhittle likelihood estimation in INAR(1) process
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. <br/>. <br/>Whittle likelihood estimation in INAR(1) processdoi:10.1080/03610926.2023.2241093Communications in Statistics - Theory and Methods2023-08-03T09:32:56ZXiaoqiang ZengGraduate School of Economics and Business, Hokkaido University, Sapporo, JapanCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2241093https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2241093?af=REstimating parameters of the gamma distribution easily and efficiently
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. <br/>. <br/>Estimating parameters of the gamma distribution easily and efficientlydoi:10.1080/03610926.2023.2241097Communications in Statistics - Theory and Methods2023-08-03T09:50:21ZZhou JunmeiLi Liqina Key Laboratory of Data Science and Smart Education, Hainan Normal University, Ministry of Education, Haikou, Hainan, Chinab School of Mathematics and Statistics, Hainan Normal University, Haikou, Hainan, ChinaCommunications in Statistics - Theory and Methods1910.1080/03610926.2023.2241097https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2241097?af=RHamming distances of tight orthogonal arrays
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239395?af=R
. <br/>. <br/>Hamming distances of tight orthogonal arraysdoi:10.1080/03610926.2023.2239395Communications in Statistics - Theory and Methods2023-08-04T08:53:23ZShanqi PangMengqian ChenXiao ZhangCollege of Mathematics and Information Science, Henan Normal University, Xinxiang, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2239395https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239395?af=RChover’s law of the iterated logarithm for weighted sums under sub-linear expectations
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. <br/>. <br/>Chover’s law of the iterated logarithm for weighted sums under sub-linear expectationsdoi:10.1080/03610926.2023.2239399Communications in Statistics - Theory and Methods2023-08-04T10:19:53ZXue DingYong ZhangSchool of Mathematics, Jilin University, Changchun, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2239399https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239399?af=RConvergence of parameter estimation of a Gaussian mixture model minimizing the Gini index of dissimilarity
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. <br/>. <br/>Convergence of parameter estimation of a Gaussian mixture model minimizing the Gini index of dissimilaritydoi:10.1080/03610926.2023.2239396Communications in Statistics - Theory and Methods2023-08-04T11:22:49ZAdriana Laura López LobatoMartha Lorena Avendaño GarridoFacultad de Matemáticas, Universidad Veracruzana, MéxicoCommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2239396https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239396?af=RConsistent ridge estimation for replicated ultrastructural measurement error models
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239403?af=R
. <br/>. <br/>Consistent ridge estimation for replicated ultrastructural measurement error modelsdoi:10.1080/03610926.2023.2239403Communications in Statistics - Theory and Methods2023-08-08T11:32:14ZGülesen Üstündağ ŞirayDepartment of Statistics, Faculty of Science and Letters, Çukurova University, Adana, TurkeyCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2239403https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239403?af=RDiagnostics for partially linear measurement error models
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242983?af=R
. <br/>. <br/>Diagnostics for partially linear measurement error modelsdoi:10.1080/03610926.2023.2242983Communications in Statistics - Theory and Methods2023-08-08T05:44:38ZHadi EmamiDepartment of Statistics, University of Kurdistan, Sanandaj, IranCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2242983https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242983?af=RA novel sample variance formula and Sv-plot3 for testing hypotheses
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. <br/>. <br/>A novel sample variance formula and Sv-plot3 for testing hypothesesdoi:10.1080/03610926.2023.2239965Communications in Statistics - Theory and Methods2023-08-09T06:03:44ZUditha Amarananda WijesuriyaDepartment of Mathematical Sciences, University of Southern Indiana, Evansville, Indiana, USACommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2239965https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239965?af=RConstruction of asymmetric orthogonal arrays of high strength via generator matrix
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242982?af=R
. <br/>. <br/>Construction of asymmetric orthogonal arrays of high strength via generator matrixdoi:10.1080/03610926.2023.2242982Communications in Statistics - Theory and Methods2023-08-09T11:53:57ZTian-Fang ZhangYingxing DuanJian-Feng Yanga College of Mathematics and Statistics, Jiangxi Normal University, Nanchang, Chinab Jiujiang Third Middle School, Jiujiang, Chinac School of Statistics and Data Science, LPMC & KLMDASR Nankai University, Tianjin, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2242982https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242982?af=RNegation of a probability distribution: An information theoretic analysis
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242986?af=R
. <br/>. <br/>Negation of a probability distribution: An information theoretic analysisdoi:10.1080/03610926.2023.2242986Communications in Statistics - Theory and Methods2023-08-10T08:10:27ZManpreet KaurAmit SrivastavaDepartment of Mathematics, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India.Communications in Statistics - Theory and Methods11610.1080/03610926.2023.2242986https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242986?af=ROn interval estimation methods for the location parameter of the Weibull distribution: An application to alloy material fatigue failure data
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. <br/>. <br/>On interval estimation methods for the location parameter of the Weibull distribution: An application to alloy material fatigue failure datadoi:10.1080/03610926.2023.2242984Communications in Statistics - Theory and Methods2023-08-10T12:14:33ZXiaoyu YangLiyang XieJiaxin SongBingfeng ZhaoYuan Lia School of Mechanical Engineering and Automation, Northeastern University, Shenyang, P.R. Chinab Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education, Northeastern University, Shenyang, P.R. Chinac School of Aeronautics and Institute of Extreme Mechanics, Northwestern Polytechnical University, Xi’an, P.R. ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2242984https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2242984?af=RExponential method of estimation in sampling theory under robust quantile regression methods
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2243529?af=R
. <br/>. <br/>Exponential method of estimation in sampling theory under robust quantile regression methodsdoi:10.1080/03610926.2023.2243529Communications in Statistics - Theory and Methods2023-08-11T06:54:35ZVinay Kumar YadavShakti PrasadDepartment of Basic and Applied Science, National Institute of Technology Arunachal Pradesh, Jote, IndiaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2243529https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2243529?af=RSome properties of q-Gaussian distributions
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. <br/>. <br/>Some properties of q-Gaussian distributionsdoi:10.1080/03610926.2023.2244097Communications in Statistics - Theory and Methods2023-08-14T10:35:54ZBen Mrad OumaimaAfif MasmoudiYousri Slaouia Laboratory of Probability and Statistics, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisiab Laboratory of Mathematics and Applications, University of Poitiers, Poitiers, FranceCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2244097https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244097?af=ROn the maxima of non stationary random fields subject to missing observations
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. <br/>. <br/>On the maxima of non stationary random fields subject to missing observationsdoi:10.1080/03610926.2023.2244098Communications in Statistics - Theory and Methods2023-08-16T12:30:21ZShengchao ZhengZhongquan TanCollege of Data Science, Jiaxing University, Jiaxing, PR ChinaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2244098https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244098?af=RA note on the exponentiation approximation of the birthday paradox
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. <br/>. <br/>A note on the exponentiation approximation of the birthday paradoxdoi:10.1080/03610926.2023.2245086Communications in Statistics - Theory and Methods2023-08-16T04:31:40ZKaiji MotegiSejun Wooa Graduate School of Economics, Kobe University, Kobe, Hyogo, Japan; b Graduate School of Business Administration, Keio University, Yokohama, Kanagawa, JapanCommunications in Statistics - Theory and Methods11010.1080/03610926.2023.2245086https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2245086?af=RExact sampling distribution of the general case sample correlation matrix
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244622?af=R
. <br/>. <br/>Exact sampling distribution of the general case sample correlation matrixdoi:10.1080/03610926.2023.2244622Communications in Statistics - Theory and Methods2023-08-17T06:12:36ZNicy SebastianT. Princya Department of Statistics, St. Thomas College, Thrissur affiliated to the University of Calicut, Kerala, Indiab Department of Statistics, Cochin University of Science and Technology, Kerala, IndiaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2244622https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244622?af=ROn the effect of items measuring different factors across individuals on item inter-correlations
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. <br/>. <br/>On the effect of items measuring different factors across individuals on item inter-correlationsdoi:10.1080/03610926.2023.2244100Communications in Statistics - Theory and Methods2023-08-18T12:59:57ZAndré BeauducelNorbert HilgerInstitute of Psychology, University of Bonn, Bonn, GermanyCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2244100https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244100?af=RThe use of the Karhunen Loève expansion in the design of computer experiments
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. <br/>. <br/>The use of the Karhunen Loève expansion in the design of computer experimentsdoi:10.1080/03610926.2023.2245085Communications in Statistics - Theory and Methods2023-08-18T01:22:10ZNoha YoussefMathematics and Actuarial Science Department, The American University in Cairo, Cairo, EgyptCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2245085https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2245085?af=RAdjusted empirical likelihood for probability density functions under strong mixing samples
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246088?af=R
. <br/>. <br/>Adjusted empirical likelihood for probability density functions under strong mixing samplesdoi:10.1080/03610926.2023.2246088Communications in Statistics - Theory and Methods2023-08-18T02:14:27ZJie TangYongsong QinDepartment of Statistics, Guangxi Normal University Guilin, Guangxi, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2246088https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246088?af=RBernstein copula characteristic function
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. <br/>. <br/>Bernstein copula characteristic functiondoi:10.1080/03610926.2023.2247107Communications in Statistics - Theory and Methods2023-08-18T02:22:12ZTarik BahraouiDépartement de Mathématiques, Université du Québec à Montrèal, Montreal, Quebec, CanadaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2247107https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2247107?af=RDifferentially private estimation in a class of bipartite graph models
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246090?af=R
. <br/>. <br/>Differentially private estimation in a class of bipartite graph modelsdoi:10.1080/03610926.2023.2246090Communications in Statistics - Theory and Methods2023-08-21T11:36:22ZLu PanJianwei HuDepartment of Statistics, Central China Normal University, Wuhan, ChinaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2246090https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246090?af=RWavelet estimation of norms for a probability density with negatively dependent biased data
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246607?af=R
. <br/>. <br/>Wavelet estimation of norms for a probability density with negatively dependent biased datadoi:10.1080/03610926.2023.2246607Communications in Statistics - Theory and Methods2023-08-21T11:42:19ZJunlian XuLu HaoSchool of Mathematics and Information Science, Baoji University of Arts and Sciences, Baoji, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2246607https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246607?af=RExtended Glivenko—Cantelli theorem for simple random sampling without replacement from a finite population
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2238233?af=R
. <br/>. <br/>Extended Glivenko—Cantelli theorem for simple random sampling without replacement from a finite populationdoi:10.1080/03610926.2023.2238233Communications in Statistics - Theory and Methods2023-07-27T05:25:58ZHitoshi Motoyamaa Delft Institute of Applied Mathematics, Delft University of Technology, Delft, Netherlandsb College of Economics, Aoyama Gakuin University, Tokyo, Japanc Risk Analysis Research Center, The Institute of Statistical Mathematics, Tokyo, JapanCommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2238233https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2238233?af=RZero-inflated logit probit model: a novel model for binary data
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. <br/>. <br/>Zero-inflated logit probit model: a novel model for binary datadoi:10.1080/03610926.2023.2248325Communications in Statistics - Theory and Methods2023-08-24T01:14:26ZKim-Hung PhoFractional Calculus, Optimization and Algebra Research Group, Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, VietnamCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2248325https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248325?af=RBayesian analysis of mixture models with Yeo-Johnson transformation
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. <br/>. <br/>Bayesian analysis of mixture models with Yeo-Johnson transformationdoi:10.1080/03610926.2023.2248326Communications in Statistics - Theory and Methods2023-08-24T01:26:19ZJingheng CaiXiaoli XuDepartment of Statistics, Sun Yat-sen University, Guangzhou, ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2248326https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248326?af=RA modified uncertain maximum likelihood estimation with applications in uncertain statistics
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248534?af=R
. <br/>. <br/>A modified uncertain maximum likelihood estimation with applications in uncertain statisticsdoi:10.1080/03610926.2023.2248534Communications in Statistics - Theory and Methods2023-08-24T01:35:02ZYang LiuBaoding Liua School of Economics and Management, Beihang University, Beijing, Chinab Department of Mathematical Sciences, Tsinghua University, Beijing, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2248534https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248534?af=RReproducible learning for accelerated failure time models via deep knockoffs
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2247508?af=R
. <br/>. <br/>Reproducible learning for accelerated failure time models via deep knockoffsdoi:10.1080/03610926.2023.2247508Communications in Statistics - Theory and Methods2023-08-26T06:20:06ZJinzhao YuDaoji LiLin LuoHui Zhaoa School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, Chinab Department of Information Systems and Decision Sciences, California State University, Fullerton, California, USAc College of Science, Zhongyuan University of Technology, Zhengzhou, ChinaCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2247508https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2247508?af=RA new frailty-based GEE approach of the informatively case K interval-censored failure time data
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. <br/>. <br/>A new frailty-based GEE approach of the informatively case K interval-censored failure time datadoi:10.1080/03610926.2023.2247505Communications in Statistics - Theory and Methods2023-08-26T12:00:19ZBo ZhaoShuying WangChunjie WangSchool of Mathematics and Statistics, Changchun University of Technology, Changchun, ChinaCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2247505https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2247505?af=RQuantile-based PLS-SEM with bag of little bootstraps
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248324?af=R
. <br/>. <br/>Quantile-based PLS-SEM with bag of little bootstrapsdoi:10.1080/03610926.2023.2248324Communications in Statistics - Theory and Methods2023-08-26T12:04:14ZHao ChengNational Academy of Innovation Strategy, China Association for Science and Technology, Beijing, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2248324https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248324?af=RA first-order Stein characterization for absolutely continuous bivariate distributions
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. <br/>. <br/>A first-order Stein characterization for absolutely continuous bivariate distributionsdoi:10.1080/03610926.2023.2250485Communications in Statistics - Theory and Methods2023-08-29T02:42:59ZLester Charles A. UmaliRichard B. EdenTimothy Robin Y. Tenga Department of Mathematics, Ateneo de Manila University, Quezon City, Philippinesb Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños, Laguna, PhilippinesCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2250485https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250485?af=RTwo-stage shrunken least squares estimator and its superiority
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250487?af=R
. <br/>. <br/>Two-stage shrunken least squares estimator and its superioritydoi:10.1080/03610926.2023.2250487Communications in Statistics - Theory and Methods2023-08-29T02:45:03ZQuanhong SongLichun WangLiqun Wanga Department of Statistics, Beijing Jiaotong University, Beijing, Chinab Department of Statistics, University of Manitoba, Winnipeg, Manitoba, CanadaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2250487https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250487?af=RPartially balanced bipartite block designs
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2251623?af=R
. <br/>. <br/>Partially balanced bipartite block designsdoi:10.1080/03610926.2023.2251623Communications in Statistics - Theory and Methods2023-08-29T02:54:06ZVinayaka .Rajender ParsadB. N. MandalSukanta DashVinaykumar L. N.Mukesh KumarD. R. Singha Graduate School, ICAR-Indian Agricultural Research Institute, Pusa, New Delhi, Indiab ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi, Indiac ICAR-Indian Agricultural Research Institute, Hazaribagh, Jharkhand, Indiad ICAR-Indian Agricultural Research Institute, Pusa, New Delhi, IndiaCommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2251623https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2251623?af=REstimating transition intensity rate on interval-censored data using semi-parametric with EM algorithm approach
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. <br/>. <br/>Estimating transition intensity rate on interval-censored data using semi-parametric with EM algorithm approachdoi:10.1080/03610926.2023.2239397Communications in Statistics - Theory and Methods2023-08-30T06:47:53ZChen QianDeo Kumar SrivastavaJianmin PanMelissa M. HudsonShesh N. Raia Biostatistics and Bioinformatics Facility, James Graham Brown Cancer Center, University of Louisville, Louisville, Kentucky, 40202, USAb Department of Biostatistics and Bioinformatics, University of Louisville, Louisville, Kentucky, 40202, USAc AbbVie Inc, North Chicago, Illinois, 60064, USAd Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USAe Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, Ohio, 45267, USAf Cancer Data Science Center, Department of Environmental and Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, Ohio, 45267, USAg Department of Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee, 38105, USAh Biostatistics and Informatics Shared Resources, University of Cincinnati Cancer Center, Cincinnati, Ohio, 45267, USACommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2239397https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2239397?af=RA new uncertainty measure via belief Rényi entropy in Dempster-Shafer theory and its application to decision making
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. <br/>. <br/>A new uncertainty measure via belief Rényi entropy in Dempster-Shafer theory and its application to decision makingdoi:10.1080/03610926.2023.2253342Communications in Statistics - Theory and Methods2023-09-01T01:28:13ZZhe LiuYu CaoXiangli YangLusi Liua School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysiab School of Cyberspace Security, Hainan University, Haikou, Chinac School of Computer Science and Technology, Hainan University, Haikou, Chinad College of Information Technology, Hainan College of Economics and Business, Haikou, ChinaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2253342https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253342?af=RHermite-Hadamard and Fejér-type inequalities for generalized η-convex stochastic processes
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. <br/>. <br/>Hermite-Hadamard and Fejér-type inequalities for generalized η-convex stochastic processesdoi:10.1080/03610926.2023.2218506Communications in Statistics - Theory and Methods2023-06-06T05:21:49ZJaya BishtRohan MishraA. Hamdia Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi, Indiab Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, Indiac Mathematics Program, Department of Mathematics, Statistics and Physics College of Arts and Sciences, Qatar University, Doha, QatarCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2218506https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2218506?af=RA generalized Burr mixture autoregressive models for modeling non linear time series
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2252121?af=R
. <br/>. <br/>A generalized Burr mixture autoregressive models for modeling non linear time seriesdoi:10.1080/03610926.2023.2252121Communications in Statistics - Theory and Methods2023-09-04T10:38:31ZVictor Jian Ming LowWooi Chen KhooHooi Ling Khooa Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Jalan Sungai Long, Kajang, Selangor, Malaysiab Department of Applied Statistics, Sunway University, Selangor, Darul Ehsan, MalaysiaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2252121https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2252121?af=ROracle inequalities for weighted group Lasso in high-dimensional Poisson regression model
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. <br/>. <br/>Oracle inequalities for weighted group Lasso in high-dimensional Poisson regression modeldoi:10.1080/03610926.2023.2253940Communications in Statistics - Theory and Methods2023-09-05T11:03:57ZLing Penga School of Statistics and Data Science, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, Chinab Key Laboratory of Data Science in Finance and Economics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, ChinaCommunications in Statistics - Theory and Methods12710.1080/03610926.2023.2253940https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253940?af=RRobust estimators of functional single index models for longitudinal data
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253939?af=R
. <br/>. <br/>Robust estimators of functional single index models for longitudinal datadoi:10.1080/03610926.2023.2253939Communications in Statistics - Theory and Methods2023-09-07T10:09:08ZYang SunXiangzhong FangSchool of Mathematical Sciences, Peking University, Beijing, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2253939https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253939?af=RConcentration inequalities of MLE and robust MLE
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253945?af=R
. <br/>. <br/>Concentration inequalities of MLE and robust MLEdoi:10.1080/03610926.2023.2253945Communications in Statistics - Theory and Methods2023-09-07T10:11:04ZXiaowei YangXinqiao LiuHaoyu Weia College of Mathematics, Sichuan University, Chengdu, Chinab School of Education, Tianjin University, Tianjin, Chinac Department of Economics, University of California San Diego, La Jolla, California, USACommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2253945https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253945?af=RA study on utilization of a cold standby component to enhance the mean residual life function of a coherent system
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. <br/>. <br/>A study on utilization of a cold standby component to enhance the mean residual life function of a coherent systemdoi:10.1080/03610926.2023.2255323Communications in Statistics - Theory and Methods2023-09-08T03:58:04ZAchintya RoyNitin Guptaa Department of Mathematics, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, Indiab Department of Mathematics and Basic Sciences, NIIT University, Neemrana, Rajasthan, IndiaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2255323https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2255323?af=RDecomposition of measure from symmetry for analyzing collapsed ordinal square contingency tables
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2233152?af=R
. <br/>. <br/>Decomposition of measure from symmetry for analyzing collapsed ordinal square contingency tablesdoi:10.1080/03610926.2023.2233152Communications in Statistics - Theory and Methods2023-07-24T01:20:49ZSatoru ShinodaKouji YamamotoSadao Tomizawaa Department of Biostatistics, Yokohama City University, School of Medicine, Yokohama City, Kanagawa, Japan; b Department of Information Science, Meisei University, Hino City, Tokyo, JapanCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2233152https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2233152?af=REstimating powers of the scale parameters under order restriction for two shifted exponential populations with a common location
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. <br/>. <br/>Estimating powers of the scale parameters under order restriction for two shifted exponential populations with a common locationdoi:10.1080/03610926.2023.2248533Communications in Statistics - Theory and Methods2023-09-11T02:06:23ZPravash JenaManas Ranjan TripathyDepartment of Mathematics, National Institute of Technology Rourkela, Rourkela, IndiaCommunications in Statistics - Theory and Methods13810.1080/03610926.2023.2248533https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2248533?af=RHow to use randomized response survey data at hand by a specific procedure to judge its efficiency versus a possible rival
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. <br/>. <br/>How to use randomized response survey data at hand by a specific procedure to judge its efficiency versus a possible rivaldoi:10.1080/03610926.2023.2250489Communications in Statistics - Theory and Methods2023-08-30T07:19:45ZArijit ChaudhuriDipika Patraa Indian Statistical Institute (ISI) Kolkata, Kolkata, West Bengal, Indiab Seth Anandram Jaipuria College, Kolkata, West Bengal, IndiaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2250489https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250489?af=RAnalysis of a GIX/M/1 queue with two-stage vacation policy using shift operator method
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. <br/>. <br/>Analysis of a GIX/M/1 queue with two-stage vacation policy using shift operator methoddoi:10.1080/03610926.2023.2250488Communications in Statistics - Theory and Methods2023-09-12T11:12:18ZYufei LiuQingqing YeJunnai Yana School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Chinab The Department of Basic Education, Linzhou College of Architectural Technology, Linzhou, ChinaCommunications in Statistics - Theory and Methods13010.1080/03610926.2023.2250488https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250488?af=RNon parametric multivariate distribution estimation under right censoring
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. <br/>. <br/>Non parametric multivariate distribution estimation under right censoringdoi:10.1080/03610926.2023.2251624Communications in Statistics - Theory and Methods2023-09-13T08:00:51ZAdil NafiiTaoufik BouezmarniMhamed Mesfiouia Département de mathématiques, Université de Sherbrooke, Sherbrooke, Québec, Canadab Département de mathématiques et d’informatique, Université de Québec à Trois-Rivières, Trois-Rivières, Québec, CanadaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2251624https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2251624?af=RCalibration estimation of subpopulation total for direct and indirect situations
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. <br/>. <br/>Calibration estimation of subpopulation total for direct and indirect situationsdoi:10.1080/03610926.2023.2256437Communications in Statistics - Theory and Methods2023-09-13T08:12:49ZAshutosh AshutoshUsman ShahzadNadia H. Al Noora Department of Statistics, Faculty of Science & Technology, MGKVP, Varanasi, Indiab Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistanc Department of Mathematics, College of Science, Mustansiriyah University, Baghdad, IraqCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2256437https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2256437?af=RAn extended Markov-switching model approach to latent heterogeneity in departmentalized manpower systems
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. <br/>. <br/>An extended Markov-switching model approach to latent heterogeneity in departmentalized manpower systemsdoi:10.1080/03610926.2023.2255322Communications in Statistics - Theory and Methods2023-09-14T06:32:08ZEverestus O. OssaiUchenna C. NdukaMbanefo S. MadukaifeAkaninyene U. UdomSamson O. UgwuDepartment of Statistics, University of Nigeria, Nsukka, NigeriaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2255322https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2255322?af=RNew bounds on entropies based on order statistics and Gini’s mean difference
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. <br/>. <br/>New bounds on entropies based on order statistics and Gini’s mean differencedoi:10.1080/03610926.2023.2256438Communications in Statistics - Theory and Methods2023-09-15T06:30:09ZXuehua YinSchool of Statistics and Data Science, Qufu Normal University, Qufu, Shandong 273165, ChinaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2256438https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2256438?af=RA combined adaptive double sampling and variable sampling interval control chart for monitoring three-level products
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. <br/>. <br/>A combined adaptive double sampling and variable sampling interval control chart for monitoring three-level productsdoi:10.1080/03610926.2023.2256439Communications in Statistics - Theory and Methods2023-09-19T09:55:44ZM. S. Mehdi KatebiAbdur Rahima Department of Statistics, Allameh Tabataba’i University, Tehran, Iranb Department of Quantitative Methods, Faculty of Business Administration, University of New Brunswick, Saint John, New Brunswick, CanadaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2256439https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2256439?af=RNew heteroscedasticity-adjusted ridge estimators in linear regression model
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. <br/>. <br/>New heteroscedasticity-adjusted ridge estimators in linear regression modeldoi:10.1080/03610926.2023.2258427Communications in Statistics - Theory and Methods2023-09-19T09:57:12ZIrum Sajjad DarSohail ChandCollege of Statistical Sciences, University of the Punjab, Lahore, PakistanCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2258427https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2258427?af=RFurther research on complete integral convergence for moving average process of ND random variables under sub-linear expectations
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. <br/>. <br/>Further research on complete integral convergence for moving average process of ND random variables under sub-linear expectationsdoi:10.1080/03610926.2023.2258428Communications in Statistics - Theory and Methods2023-09-19T09:57:14ZXiaocong ChenQunying WuCollege of Science, Guilin University of Technology, Guilin, PR ChinaCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2258428https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2258428?af=RA calibration-based approach on estimation of mean of a stratified population in the presence of non response
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. <br/>. <br/>A calibration-based approach on estimation of mean of a stratified population in the presence of non responsedoi:10.1080/03610926.2023.2257818Communications in Statistics - Theory and Methods2023-09-20T10:35:06ZManoj K. ChaudharyBasant K. RayGautam K. VishwakarmaCem Kadilara Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, Indiab Department of Statistics, Hacettepe University, Ankara, TurkeyCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2257818https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2257818?af=RA new bivariate distribution with uniform marginals
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253944?af=R
. <br/>. <br/>A new bivariate distribution with uniform marginalsdoi:10.1080/03610926.2023.2253944Communications in Statistics - Theory and Methods2023-09-21T11:00:30ZAsok K. NandaShovan ChowdhurySanjib GayenSubarna Bhattacharjeea Department of Mathematics and Statistics, Indian Institute of Science Education and Research Kolkata, West Bengal, Indiab Quantitative Methods and Operations Management Area, Indian Institute of Management, Kozhikode, Kerala, Indiac Department of Mathematics, Gurudas College, Narkeldanga, Kolkata, West Bengal, Indiad Department of Mathematics, Ravenshaw University, Cuttack, Odisha, IndiaCommunications in Statistics - Theory and Methods12610.1080/03610926.2023.2253944https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2253944?af=RRobustness of clustering coefficients
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. <br/>. <br/>Robustness of clustering coefficientsdoi:10.1080/03610926.2023.2259525Communications in Statistics - Theory and Methods2023-09-22T12:50:03ZXiaofeng ZhaoMingao Yuana School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou, Henan, Chinab Department of Statistics, North Dakota State University, Fargo, North Dakota, USACommunications in Statistics - Theory and Methods13710.1080/03610926.2023.2259525https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2259525?af=RExponentially quantile regression-ratio-type estimators for robust mean estimation
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. <br/>. <br/>Exponentially quantile regression-ratio-type estimators for robust mean estimationdoi:10.1080/03610926.2023.2258426Communications in Statistics - Theory and Methods2023-09-25T10:28:37ZMemoona KhalidHina KhanaJavid Shabbira Department of Statistics, Government College University, Lahore, Pakistan; b Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan; c Department of Statistics, University of Wah, Wah Cantt., PakistanCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2258426https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2258426?af=RA composite Bayesian approach for quantile curve fitting with non-crossing constraints
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. <br/>. <br/>A composite Bayesian approach for quantile curve fitting with non-crossing constraintsdoi:10.1080/03610926.2023.2259524Communications in Statistics - Theory and Methods2023-09-26T05:25:04ZQiao WangZhongheng Caia Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USAb Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, Tennessee, USACommunications in Statistics - Theory and Methods12510.1080/03610926.2023.2259524https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2259524?af=RA population model with Markovian arrival process and binomial correlated catastrophes
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2261059?af=R
. <br/>. <br/>A population model with Markovian arrival process and binomial correlated catastrophesdoi:10.1080/03610926.2023.2261059Communications in Statistics - Theory and Methods2023-09-28T11:27:50ZNitin KumarDepartment of Mathematics, Indian Institute of Technology Jammu, Jammu, IndiaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2261059https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2261059?af=ROn generalized f-statistics
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. <br/>. <br/>On generalized f-statisticsdoi:10.1080/03610926.2023.2263112Communications in Statistics - Theory and Methods2023-10-03T01:42:15ZQuentin BarthélemyFoxstream, Rue du Dauphiné, Vaulx-en-Velin, FranceCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2263112https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263112?af=RAutocorrelated unreplicated linear functional relationship model for multivariate time series data
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263110?af=R
. <br/>. <br/>Autocorrelated unreplicated linear functional relationship model for multivariate time series datadoi:10.1080/03610926.2023.2263110Communications in Statistics - Theory and Methods2023-10-04T06:05:58ZYun Fah ChangSing Yan LooiWei Yeing PanShin Zhu Sima School of Accounting and Finance, Taylor’s University, Subang Jaya, Malaysiab Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Kampar, Malaysiac Department of Mathematical and Actuarial Sciences, LKC Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kampar, Malaysiad School of Mathematical Sciences, University of Nottingham Malaysia, Semenyih, MalaysiaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2263110https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263110?af=RShort proof of posterior robustness: An illustration of basic ideas in a simple case
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. <br/>. <br/>Short proof of posterior robustness: An illustration of basic ideas in a simple casedoi:10.1080/03610926.2023.2263113Communications in Statistics - Theory and Methods2023-10-04T06:10:15ZYasuyuki HamuraGraduate School of Economics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto, JapanCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2263113https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263113?af=RA note on statistical analysis of Cpk for autocorrelated data in the presence of random measurement errors
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. <br/>. <br/>A note on statistical analysis of Cpk for autocorrelated data in the presence of random measurement errorsdoi:10.1080/03610926.2023.2263115Communications in Statistics - Theory and Methods2023-10-04T06:11:19ZKuntal BeraM.Z. AnisSQC & OR Unit, Indian Statistical Institute, Kolkata, IndiaCommunications in Statistics - Theory and Methods1610.1080/03610926.2023.2263115https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263115?af=REstimation of zero-inflated bivariate Poisson regression with missing covariates
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. <br/>. <br/>Estimation of zero-inflated bivariate Poisson regression with missing covariatesdoi:10.1080/03610926.2023.2262637Communications in Statistics - Theory and Methods2023-10-06T05:55:48ZKonan Jean Geoffroy KouakouOuagnina HiliJean-François Dupuya UMRI-Mathématiques et Nouvelles Technologies de l’Information, INPHB-Yamoussoukro, Côte d’Ivoireb Univ Rennes, INSA Rennes, CNRS, IRMAR - UMR 6625, Rennes, FranceCommunications in Statistics - Theory and Methods12810.1080/03610926.2023.2262637https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2262637?af=RMoments of inverse Weibull-geometric distribution based on progressive type-II right censored order statistics
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263117?af=R
. <br/>. <br/>Moments of inverse Weibull-geometric distribution based on progressive type-II right censored order statisticsdoi:10.1080/03610926.2023.2263117Communications in Statistics - Theory and Methods2023-10-06T06:45:47ZAreej M. AL-ZaydiBander Al-Zahrania Department of Mathematics and Statistics, Taif University, Taif, Saudi Arabiab Department of Statistics, King Abdulaziz University, Jeddah, Saudi ArabiaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2263117https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263117?af=RAn innovation mortality prediction model with cohort effect
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264998?af=R
. <br/>. <br/>An innovation mortality prediction model with cohort effectdoi:10.1080/03610926.2023.2264998Communications in Statistics - Theory and Methods2023-10-06T07:05:57ZHongmin XiaoMiaomiao ZhaoXiang LiAiqin BaiCollege of Mathematics and Statistics, Northwest Normal University, Lanzhou, Gansu, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2264998https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264998?af=RHyper Markov law in undirected graphical models with its applications
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. <br/>. <br/>Hyper Markov law in undirected graphical models with its applicationsdoi:10.1080/03610926.2023.2263111Communications in Statistics - Theory and Methods2023-10-09T02:31:16ZXiong KangBrian Yi SunCollege of Mathematics and Systems Science, Xinjiang University, Urumqi 80049, Xinjiang, P.R. ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2263111https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263111?af=RA note on switching eigenvalues under small perturbations
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. <br/>. <br/>A note on switching eigenvalues under small perturbationsdoi:10.1080/03610926.2023.2263114Communications in Statistics - Theory and Methods2023-10-09T02:34:47ZMarina MasiotiConnie S. N. Li-Wai-SuenLuke A. PrendergastAmanda Shakera Department of Mathematical and Physical Sciences, La Trobe University, Melbourne, Victoria, Australiab Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, AustraliaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2263114https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263114?af=R
Lr convergence for arrays of rowwise m-extended negatively dependent random variables
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. <br/>. <br/>
Lr convergence for arrays of rowwise m-extended negatively dependent random variablesdoi:10.1080/03610926.2023.2263600Communications in Statistics - Theory and Methods2023-10-09T03:03:07ZZi-jian WangYi WuYue DuXue-jun Wanga School of Big Data and Statistics, Anhui University, Hefei, P.R. Chinab School of Big Data and Artificial Intelligence, Chizhou University, Chizhou, P.R. ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2263600https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263600?af=RComplete convergence for randomly weighted sums of dependent random variables and an application
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2262636?af=R
. <br/>. <br/>Complete convergence for randomly weighted sums of dependent random variables and an applicationdoi:10.1080/03610926.2023.2262636Communications in Statistics - Theory and Methods2023-10-10T06:51:26ZPingyan ChenJingjing LuoSoo Hak Sunga Department of Mathematics, Jinan University, Guangzhou, P.R. Chinab Department of Applied Mathematics, Pai Chai University, Daejeon, South KoreaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2262636https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2262636?af=RComplete f-moment convergence for randomly weighted sums of extended negatively dependent random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264992?af=R
. <br/>. <br/>Complete f-moment convergence for randomly weighted sums of extended negatively dependent random variablesdoi:10.1080/03610926.2023.2264992Communications in Statistics - Theory and Methods2023-10-11T08:32:06ZMeimei GeYongfeng WuXin Denga School of Big Data and Statistics, Anhui University, Hefei, P.R. Chinab School of Mathematics and Finance, Chuzhou University, Chuzhou, P.R. Chinac College of Mathematics and Computer Science, Tongling University, Tongling, P.R. ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2264992https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264992?af=RFraction of design space plots for evaluating orthogonal composite designs
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. <br/>. <br/>Fraction of design space plots for evaluating orthogonal composite designsdoi:10.1080/03610926.2023.2264993Communications in Statistics - Theory and Methods2023-10-11T08:35:33ZAbimibola Victoria OladugbaBrenda Mbouamba YankamUchenna Charity OnwuamaezeDepartment of Statistics, University of Nigeria, Nsukka, NigeriaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2264993https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264993?af=RStatistical inference of multi-state transition model for longitudinal data with measurement error and heterogeneity
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. <br/>. <br/>Statistical inference of multi-state transition model for longitudinal data with measurement error and heterogeneitydoi:10.1080/03610926.2023.2264997Communications in Statistics - Theory and Methods2023-10-12T09:56:59ZJiajie QinJing Guana Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai,Chinab School of Mathematics, Tianjin University, Tianjin, ChinaCommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2264997https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264997?af=RAnalysis of M/M/1 queueing systems with negative customers and unreliable repairers
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2265000?af=R
. <br/>. <br/>Analysis of M/M/1 queueing systems with negative customers and unreliable repairersdoi:10.1080/03610926.2023.2265000Communications in Statistics - Theory and Methods2023-10-12T01:31:06ZRuiling TianYao ZhangSchool of Science, Yanshan University, Qinhuangdao, China.Communications in Statistics - Theory and Methods11410.1080/03610926.2023.2265000https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2265000?af=RA Parzen–Rosenblatt type density estimator for circular data: exact and asymptotic optimal bandwidths
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. <br/>. <br/>A Parzen–Rosenblatt type density estimator for circular data: exact and asymptotic optimal bandwidthsdoi:10.1080/03610926.2023.2264996Communications in Statistics - Theory and Methods2023-10-16T12:01:19ZCarlos TenreiroCMUC, Department of Mathematics, University of Coimbra, Coimbra, PortugalCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2264996https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264996?af=RMoment-based approximations for stochastic control model of type (s, S)
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. <br/>. <br/>Moment-based approximations for stochastic control model of type (s, S)
doi:10.1080/03610926.2023.2268765Communications in Statistics - Theory and Methods2023-10-17T09:42:09ZAslı Bektaş KamışlıkFeyrouz BaghezzeTulay KesemenTahir Khaniyeva Recep Tayyip Erdogan University, Department of Mathematics, Rize, Turkeyb Karadeniz Technical University, Department of Mathematics, Trabzon, Turkeyc TOBB University of Economics and Technology, Department of Industrial Engineering, Ankara, Turkeyd Azerbaijan State University of Economics, The Center of Digital Economics, Baku, AzerbaijanCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2268765https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2268765?af=RPenalized Mallow’s model averaging
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. <br/>. <br/>Penalized Mallow’s model averagingdoi:10.1080/03610926.2023.2264995Communications in Statistics - Theory and Methods2023-10-18T09:51:13ZYifan LiuSchool of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2264995https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2264995?af=RStochastic comparisons of the largest and smallest claim amounts with heterogeneous survival exponentiated location-scale distributed claim severities
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. <br/>. <br/>Stochastic comparisons of the largest and smallest claim amounts with heterogeneous survival exponentiated location-scale distributed claim severitiesdoi:10.1080/03610926.2023.2269440Communications in Statistics - Theory and Methods2023-10-18T10:16:14ZLongxiang FangQi ZhengYing Dinga Department of Mathematics and Statistics, Anhui Normal University, Wuhu, PR Chinab Department of Applied Mathematics, Zhejiang University of Technology, Hangzhou, PR ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2269440https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269440?af=RComparison of higher degree stop-loss transforms
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269453?af=R
. <br/>. <br/>Comparison of higher degree stop-loss transformsdoi:10.1080/03610926.2023.2269453Communications in Statistics - Theory and Methods2023-10-18T10:21:05ZIdir ArabPaulo Eduardo OliveiraBeatriz SantosCMUC, Department of Mathematics, University of Coimbra, Coimbra, PortugalCommunications in Statistics - Theory and Methods1910.1080/03610926.2023.2269453https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269453?af=REstimation of uncertainty distribution function by the principle of least squares
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269451?af=R
. <br/>. <br/>Estimation of uncertainty distribution function by the principle of least squaresdoi:10.1080/03610926.2023.2269451Communications in Statistics - Theory and Methods2023-10-19T06:54:00ZYang LiuBaoding Liua School of Economics and Management, Beihang University, Beijing, Chinab Department of Mathematical Sciences, Tsinghua University, Beijing, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2269451https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269451?af=RA better one stage multiple comparison procedure of several treatment mean lifetimes with the control for exponential distributions under heteroscedasticity
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. <br/>. <br/>A better one stage multiple comparison procedure of several treatment mean lifetimes with the control for exponential distributions under heteroscedasticitydoi:10.1080/03610926.2023.2271106Communications in Statistics - Theory and Methods2023-10-19T12:11:00ZShu-Fei WuDepartment of Statistics, Tamkang University, Taipei, TaiwanCommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2271106https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2271106?af=RAsymptotic loss of the MLE of a truncation parameter in the presence of a nuisance parameter for a one-sided truncated family of distributions
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. <br/>. <br/>Asymptotic loss of the MLE of a truncation parameter in the presence of a nuisance parameter for a one-sided truncated family of distributionsdoi:10.1080/03610926.2023.2269436Communications in Statistics - Theory and Methods2023-10-20T05:44:49ZM. AkahiraN. OhyauchiInstitute of Mathematics, University of Tsukuba, Tsukuba, Ibaraki, JapanCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2269436https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269436?af=RA correction to Begg’s test for publication bias
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2271590?af=R
. <br/>. <br/>A correction to Begg’s test for publication biasdoi:10.1080/03610926.2023.2271590Communications in Statistics - Theory and Methods2023-10-20T05:49:14ZHaben MichaelMusie Ghebremichaela University of Massachusetts, Amherst, Massachusetts, USAb Ragon Institute and Harvard University, Cambridge, Massachusetts, USACommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2271590https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2271590?af=ROrdering properties of parallel and series systems with a general lifetime family of distributions for independent components under random shocks
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. <br/>. <br/>Ordering properties of parallel and series systems with a general lifetime family of distributions for independent components under random shocksdoi:10.1080/03610926.2023.2269445Communications in Statistics - Theory and Methods2023-10-23T09:51:55ZAbed Hossein PanahiHabib JafariGhobad Saadat Kia (Barmalzan)a Department of Statistics, Razi University, Kermanshah, Iranb Department of Basic Science, Kermanshah University of Technology, Kermanshah, IranCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2269445https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269445?af=RConstruction of mixed-level fractional factorial split-plot designs with combined minimum aberration
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269442?af=R
. <br/>. <br/>Construction of mixed-level fractional factorial split-plot designs with combined minimum aberrationdoi:10.1080/03610926.2023.2269442Communications in Statistics - Theory and Methods2023-10-23T11:02:49ZHaosheng JiangChongqi Zhanga School of Economics and Statistics, Guangzhou University, Guangzhou, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2269442https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269442?af=RRandom logistic machine (RLM): Transforming statistical models into machine learning approach
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. <br/>. <br/>Random logistic machine (RLM): Transforming statistical models into machine learning approachdoi:10.1080/03610926.2023.2268767Communications in Statistics - Theory and Methods2023-10-18T10:02:24ZYu-Shan LiChao-Yu GuoDivision of Biostatistics and Data Science, Institute of Public Health, College of Medicine, National Yang Ming Chiao Tung University, Taipei, TaiwanCommunications in Statistics - Theory and Methods1910.1080/03610926.2023.2268767https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2268767?af=RAn economic-statistical design of synthetic Tukey’s control chart with Taguchi’s asymmetric loss functions under log-normal distribution
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. <br/>. <br/>An economic-statistical design of synthetic Tukey’s control chart with Taguchi’s asymmetric loss functions under log-normal distributiondoi:10.1080/03610926.2023.2269448Communications in Statistics - Theory and Methods2023-10-25T03:00:39ZPei-Hsi LeeChao-Yu Choua Department of Information Management, Chaoyang University of Technology, Wufeng, Taichung, Taiwanb Department of Finance, National Taichung University of Science and Technology, North District, Taichung, TaiwanCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2269448https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2269448?af=RPoissonian occupation times of refracted Lévy processes with applications
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2271589?af=R
. <br/>. <br/>Poissonian occupation times of refracted Lévy processes with applicationsdoi:10.1080/03610926.2023.2271589Communications in Statistics - Theory and Methods2023-10-26T10:10:31ZZaiming LiuXiaofeng YangHua Donga School of Mathematics and Statistics, Central South University, Changsha, Hunan, Chinab School of Statistics and Data Science, Qufu Normal University, Shandong, Qufu, Shandong, ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2271589https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2271589?af=RMatrix spaces and ordinary least square estimators in linear models for random matrices
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2272004?af=R
. <br/>. <br/>Matrix spaces and ordinary least square estimators in linear models for random matricesdoi:10.1080/03610926.2023.2272004Communications in Statistics - Theory and Methods2023-10-26T03:28:03ZXiaomi HuDepartment of Mathematics, Statistics and Physics, Wichita State University, Wichita, Kansas, USACommunications in Statistics - Theory and Methods11010.1080/03610926.2023.2272004https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2272004?af=ROptimal periodic dividends with penalty payments under a diffusion model
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2272002?af=R
. <br/>. <br/>Optimal periodic dividends with penalty payments under a diffusion modeldoi:10.1080/03610926.2023.2272002Communications in Statistics - Theory and Methods2023-10-27T11:54:03ZLong YangGuohe DengSchool of Mathematics and Statistics, Guangxi Normal University, Guangxi, ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2272002https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2272002?af=RLeast squares estimators for reflected Ornstein–Uhlenbeck processes
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273204?af=R
. <br/>. <br/>Least squares estimators for reflected Ornstein–Uhlenbeck processesdoi:10.1080/03610926.2023.2273204Communications in Statistics - Theory and Methods2023-10-27T11:59:46ZHan YuecaiaZhang DingwenSchool of Mathematics, Jilin University, Changchun, ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2273204https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273204?af=REstimation of treatment effects in two sample problems under general biased sampling data
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273208?af=R
. <br/>. <br/>Estimation of treatment effects in two sample problems under general biased sampling datadoi:10.1080/03610926.2023.2273208Communications in Statistics - Theory and Methods2023-10-31T11:51:28ZFangfang BaiRuiyu YangSchool of Statistics, University of International Business and Economics, Beijing, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2273208https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273208?af=RGranger non causality and predictor spaces
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2276045?af=R
. <br/>. <br/>Granger non causality and predictor spacesdoi:10.1080/03610926.2023.2276045Communications in Statistics - Theory and Methods2023-11-01T11:05:00ZUmberto TriaccaDepartment of Computer Engineering, Computer Science and Mathematics, University of L’Aquila, Coppito, ItalyCommunications in Statistics - Theory and Methods1610.1080/03610926.2023.2276045https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2276045?af=RTime-consistent strategies between two competitive DC pension plans with the return of premiums clauses and salary risk
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. <br/>. <br/>Time-consistent strategies between two competitive DC pension plans with the return of premiums clauses and salary riskdoi:10.1080/03610926.2023.2273207Communications in Statistics - Theory and Methods2023-11-02T09:58:43ZGaoqin NieXingjiang ChenHao Changa School of Statistics, Capital University of Economics and Business, Beijing, Chinab School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealandc School of Mathematical Sciences, Tiangong University, Tianjin, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2273207https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273207?af=RDoubly bounded exponential model: Some information measures and estimation
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. <br/>. <br/>Doubly bounded exponential model: Some information measures and estimationdoi:10.1080/03610926.2023.2273779Communications in Statistics - Theory and Methods2023-11-02T10:00:02ZBrijesh P. SinghUtpal Dhar DasKadir KarakayaHassan S. BakouchBadamasi Abbaa Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, Indiab Department of Mathematics, School of Basic Science and Research, Sharda University, Greater Noida, Indiac Department of Statistics, Selcuk University, Konya, Turkeyd Department of Mathematics, College of Science, Qassim University, Buraydah, Saudi Arabiae Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egyptf Department of Mathematics, Yusuf Maitama Sule University, Kano, Nigeriag School of Mathematics and Statistics, Central South University, Changsha, China.Communications in Statistics - Theory and Methods11810.1080/03610926.2023.2273779https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273779?af=RJackknife Kibria-Lukman estimator for the beta regression model
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273206?af=R
. <br/>. <br/>Jackknife Kibria-Lukman estimator for the beta regression modeldoi:10.1080/03610926.2023.2273206Communications in Statistics - Theory and Methods2023-11-03T06:12:03ZTuba KoçEmre Dündera Statistics Department, Cankiri Karatekin University, Cankiri, Turkeyb Statistics Department, Ondokuz Mayis University, Samsun, TurkeyCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2273206https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273206?af=ROptimal truncated sequential test for exponential distribution
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2274811?af=R
. <br/>. <br/>Optimal truncated sequential test for exponential distributiondoi:10.1080/03610926.2023.2274811Communications in Statistics - Theory and Methods2023-11-03T06:12:57ZMaoda FangSigui HuQiude LiHuijuan ChenRongjin LongMaoyue Yea School of Mathematic and Statistics, Guizhou University, Guiyang, Chinab School of Biology and Engineering, Guizhou Medical University, Guiyang, ChinaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2274811https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2274811?af=RStatistical properties of co-quantiles and their applications to momentum spillovers
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. <br/>. <br/>Statistical properties of co-quantiles and their applications to momentum spilloversdoi:10.1080/03610926.2023.2263116Communications in Statistics - Theory and Methods2023-10-06T06:39:47ZOh Kang KwonStephen Satchella Discipline of Finance, Codrington Building (H69), The University of Sydney, New South Wales, Australiab Trinity College, University of Cambridge, Cambridge, UKCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2263116https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2263116?af=RKernel estimators for mean residual lifetime in length-biased sampling
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2277129?af=R
. <br/>. <br/>Kernel estimators for mean residual lifetime in length-biased samplingdoi:10.1080/03610926.2023.2277129Communications in Statistics - Theory and Methods2023-11-08T12:44:02ZR. ZaminiM. AjamiS. Ghafouria Department of Mathematics, Faculty of Mathematical Sciences and Computer, Kharazmi University, Tehran, Iranb Department of Statistics, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iranc Department of Mathematics, Faculty of Sciences, Arak University, Arak, IranCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2277129https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2277129?af=RThe Bessel function expression of characteristic function
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278426?af=R
. <br/>. <br/>The Bessel function expression of characteristic functiondoi:10.1080/03610926.2023.2278426Communications in Statistics - Theory and Methods2023-11-08T12:51:09ZChuancun YinHua DongSchool of Statistics and Data Science, Qufu Normal University, Qufu, Shandong, ChinaCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2278426https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278426?af=RFeature screening for ultra-high-dimensional data via multiscale graph correlation
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2277130?af=R
. <br/>. <br/>Feature screening for ultra-high-dimensional data via multiscale graph correlationdoi:10.1080/03610926.2023.2277130Communications in Statistics - Theory and Methods2023-11-10T02:39:39ZLuojia DengJinhai WuBin ZhangYue Zhanga Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, Chinab SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, Shanghai, Chinac Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USACommunications in Statistics - Theory and Methods13810.1080/03610926.2023.2277130https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2277130?af=RGeneral weighted cumulative residual (past) extropy of minimum (maximum) ranked set sampling with unequal samples
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279910?af=R
. <br/>. <br/>General weighted cumulative residual (past) extropy of minimum (maximum) ranked set sampling with unequal samplesdoi:10.1080/03610926.2023.2279910Communications in Statistics - Theory and Methods2023-11-10T02:50:20ZSantosh Kumar ChaudharyNitin GuptaDepartment of Mathematics, Indian Institute of Technology Kharagpur, West Bengal, IndiaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2279910https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279910?af=RRevised schematic array
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279911?af=R
. <br/>. <br/>Revised schematic arraydoi:10.1080/03610926.2023.2279911Communications in Statistics - Theory and Methods2023-11-10T02:49:56ZZuolu HaoYu TangSchool of Mathematical Sciences, Soochow University, Suzhou, ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2279911https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279911?af=RA generalized class of estimators for the mean using multiauxiliary information in adaptive cluster sampling
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. <br/>. <br/>A generalized class of estimators for the mean using multiauxiliary information in adaptive cluster samplingdoi:10.1080/03610926.2023.2274809Communications in Statistics - Theory and Methods2023-11-14T01:48:10ZHousila P. SinghAnurag GuptaRajesh TailorNeha Garga School of Studies in Statistics, Vikram University, Ujjain, Indiab Indian Agricultural Statistics Research Institute, ICAR, New Delhi, Indiac School of Sciences, IGNOU, New Delhi, IndiaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2274809https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2274809?af=ROn regression analysis with Padé approximants
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278428?af=R
. <br/>. <br/>On regression analysis with Padé approximantsdoi:10.1080/03610926.2023.2278428Communications in Statistics - Theory and Methods2023-11-14T01:58:42ZGlib YevkinOlexandr Yevkina University Information Technology, York University, Toronto, Canadab Research and Development, Software for Structures, Toronto, CanadaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2278428https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278428?af=RAn extended exponential SEMIFAR model with application in R
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2276049?af=R
. <br/>. <br/>An extended exponential SEMIFAR model with application in Rdoi:10.1080/03610926.2023.2276049Communications in Statistics - Theory and Methods2023-11-15T10:04:37ZSebastian LetmatheJan BeranYuanhua Fenga Faculty of Business Administration and Economics, Paderborn University, Paderborn, Germanyb Department of Mathematics and Statistics, University of Konstanz, Konstanz, GermanyCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2276049https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2276049?af=RIdentifiability of the random effects’ covariance matrix of the linear mixed model
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2272003?af=R
. <br/>. <br/>Identifiability of the random effects’ covariance matrix of the linear mixed modeldoi:10.1080/03610926.2023.2272003Communications in Statistics - Theory and Methods2023-10-31T12:56:01ZMatteo AmestoyMark A. van de WielWessel N. van Wieringena Department of Epidemiology and Data Science, Amsterdam UMC, Amsterdam, The Netherlandsb Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, The NetherlandsCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2272003https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2272003?af=RPrecise large deviations of aggregate claims in bidimensional risk model with dependence structures
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278430?af=R
. <br/>. <br/>Precise large deviations of aggregate claims in bidimensional risk model with dependence structuresdoi:10.1080/03610926.2023.2278430Communications in Statistics - Theory and Methods2023-11-16T09:02:46ZQingwu GaoWen LiLinmin Kana School of Mathematics, Nanjing Audit University, Nanjing, Chinab School of Statistics and Data Science, Nanjing Audit University, Nanjing, ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2278430https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278430?af=RK-optimal designs for the second-order Scheffé polynomial model
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. <br/>. <br/>K-optimal designs for the second-order Scheffé polynomial modeldoi:10.1080/03610926.2023.2279914Communications in Statistics - Theory and Methods2023-11-16T10:02:52ZHaosheng JiangChongqi ZhangJiali ChenSchool of Economics and Statistics, Guangzhou University, Guangzhou, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2279914https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279914?af=RA new kernel regression approach for robustified L2 boosting
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280497?af=R
. <br/>. <br/>A new kernel regression approach for robustified L2 boostingdoi:10.1080/03610926.2023.2280497Communications in Statistics - Theory and Methods2023-11-17T08:18:30ZSuneel Babu ChatlaDepartment of Mathematical Sciences, University of Texas at El Paso, El Paso, Texas, USACommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2280497https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280497?af=RA novel method of generating distributions on the unit interval with applications
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280506?af=R
. <br/>. <br/>A novel method of generating distributions on the unit interval with applicationsdoi:10.1080/03610926.2023.2280506Communications in Statistics - Theory and Methods2023-11-17T08:30:35ZAniket BiswasSubrata ChakrabortyIndranil Ghosha Department of Statistics, Dibrugarh University, Dibrugarh, Assam, Indiab Department of Mathematics and Statistics, University of North Carolina Wilmington, Wilmington, North Carolina, USACommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2280506https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280506?af=RA sample size-dependent prior strategy for bridging the Bayesian-frequentist gap in point null hypothesis testing
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273202?af=R
. <br/>. <br/>A sample size-dependent prior strategy for bridging the Bayesian-frequentist gap in point null hypothesis testingdoi:10.1080/03610926.2023.2273202Communications in Statistics - Theory and Methods2023-11-19T06:49:37ZQiu-Hu ZhangYi-Qing Nia School of Civil Engineering and Architecture, Wuyi University, Jiangmen, Guangdong, Chinab National Engineering Research Centre on Rail Transit Electrification and Automation (Hong Kong Branch), The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Chinac Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2273202https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273202?af=RA new wavelet-based estimation of conditional density via block threshold method
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279917?af=R
. <br/>. <br/>A new wavelet-based estimation of conditional density via block threshold methoddoi:10.1080/03610926.2023.2279917Communications in Statistics - Theory and Methods2023-11-19T06:57:09ZEsmaeil ShiraziOlivier P. Faugerasa Faculty of Science, Gonbad Kavous university, Gonbad Kavous, Iranb Toulouse School of Economics, University Toulouse 1 Capitole, 1, Esplanade de l’Universite, Office T106, 31080 Toulouse Cedex 06, FranceCommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2279917https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279917?af=RComplete convergence for moving average process generated by extended negatively dependent random variables under sub-linear expectations
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. <br/>. <br/>Complete convergence for moving average process generated by extended negatively dependent random variables under sub-linear expectationsdoi:10.1080/03610926.2023.2279924Communications in Statistics - Theory and Methods2023-11-19T07:09:46ZXue DingSchool of Mathematics, Jilin University, Changchun, ChinaCommunications in Statistics - Theory and Methods12010.1080/03610926.2023.2279924https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279924?af=RNon parametric maximin aggregation for data with inhomogeneity
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. <br/>. <br/>Non parametric maximin aggregation for data with inhomogeneitydoi:10.1080/03610926.2023.2279913Communications in Statistics - Theory and Methods2023-11-21T03:03:32ZJinwen LiangMaozai TianYaohua Ronga College of Statistics and Data Science, Beijing University of Technology, Beijing, P.R. Chinab School of Statistics, Renmin University of China, Beijing, P.R. Chinac Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2279913https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279913?af=RProperties and applications of two-tailed quasi-Lindley distribution
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. <br/>. <br/>Properties and applications of two-tailed quasi-Lindley distributiondoi:10.1080/03610926.2023.2279915Communications in Statistics - Theory and Methods2023-11-22T05:57:44ZC. Satheesh KumarRosmi JoseDepartment of Statistics, University of Kerala, Trivandrum, Kerala, IndiaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2279915https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2279915?af=ROn approximation of linear regression disturbance distribution
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280539?af=R
. <br/>. <br/>On approximation of linear regression disturbance distributiondoi:10.1080/03610926.2023.2280539Communications in Statistics - Theory and Methods2023-11-22T06:03:34ZJanusz L. WywiałDepartment of Statistics, Econometrics and Mathematics, University of Economics in Katowice, Katowice, PolandCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2280539https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280539?af=RBootstrapping ARMA time series models after model selection
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. <br/>. <br/>Bootstrapping ARMA time series models after model selectiondoi:10.1080/03610926.2023.2280546Communications in Statistics - Theory and Methods2023-11-22T06:05:04ZMulubrhan G. HaileDavid J. Olivea Department of Mathematics and Physics, Westminster College, Fulton, Missouri, USAb School of Mathematical & Statistical Sciences, Southern Illinois University, Carbondale, Illinois, USACommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2280546https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280546?af=RInequality restricted estimator for gamma regression: Bayesian approach as a solution to the multicollinearity
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. <br/>. <br/>Inequality restricted estimator for gamma regression: Bayesian approach as a solution to the multicollinearitydoi:10.1080/03610926.2023.2281267Communications in Statistics - Theory and Methods2023-11-22T06:12:23ZSolmaz SeifollahiHossein BevraniKaniav Kamarya Faculty of Mathematics, Statistics and Computer Science, University of Tabriz, Tabriz, Iranb Fédération Mathématique, CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, FranceCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2281267https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281267?af=RInequalities on the ruin probability for light-tailed distributions with some restrictions
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. <br/>. <br/>Inequalities on the ruin probability for light-tailed distributions with some restrictionsdoi:10.1080/03610926.2023.2281273Communications in Statistics - Theory and Methods2023-11-22T12:46:14ZAbouzar Bazyaria Department of Statistics, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iranb Department of Mathematics, Salman Farsi University of Kazerun, Kazerun, IranCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2281273https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281273?af=RStrong consistency of parameter estimation for the CIR integrated diffusion process with long-span high-frequency data
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. <br/>. <br/>Strong consistency of parameter estimation for the CIR integrated diffusion process with long-span high-frequency datadoi:10.1080/03610926.2023.2278429Communications in Statistics - Theory and Methods2023-11-23T11:56:36ZShanchao YangShuyi LuoZhiyong LiJiaying XieXin Yanga School of Mathematics and Statistics, Guangxi Normal University, Guilin, Chinab School of Mathematical Sciences, Guilin University of Aerospace Technology, Guilin, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2278429https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2278429?af=RA relationship between orthogonal regression and the coefficient of determination under rotation of data sets
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. <br/>. <br/>A relationship between orthogonal regression and the coefficient of determination under rotation of data setsdoi:10.1080/03610926.2023.2281897Communications in Statistics - Theory and Methods2023-11-24T06:01:50ZGregory RhoadsEric MarlandJose Almer SanquiMichael BosséWilliam BauldryDepartment of Mathematical Sciences, Appalachian State University, Boone, North Carolina, USACommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2281897https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281897?af=RExperience rating of risk premium for Esscher premium principle
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. <br/>. <br/>Experience rating of risk premium for Esscher premium principledoi:10.1080/03610926.2023.2286192Communications in Statistics - Theory and Methods2023-11-25T12:03:23ZYi ZhangLimin Wena School of Finance, Jiangxi Normal University, Nanchang, Chinab Research Center of Management Science and Engineering, Jiangxi Normal University, Nanchang, Chinac School of Mathematics and Statistics, Jiangxi Normal University, Nanchang, ChinaCommunications in Statistics - Theory and Methods12910.1080/03610926.2023.2286192https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2286192?af=RThe Legendre transform-dual-asymptotic solution for optimal investment strategy with random incomes
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. <br/>. <br/>The Legendre transform-dual-asymptotic solution for optimal investment strategy with random incomesdoi:10.1080/03610926.2023.2281896Communications in Statistics - Theory and Methods2023-11-24T11:25:52ZJinyang LiuSheng LiYong HeBoping TianLi Denga School of Mathematics, Harbin Institute of Technology, Harbin, Chinab School of Statistics, Chengdu University of Information Technology, Chengdu, Chinac School of Mathematics, Physics and Data Science, Chongqing University of Science and Technology, Chongqing, Chinad Sichuan Vocational College of Finance and Economics, Chengdu, ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2281896https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281896?af=RRobust reinsurance contract and investment with delay under mean-variance framework
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2282380?af=R
. <br/>. <br/>Robust reinsurance contract and investment with delay under mean-variance frameworkdoi:10.1080/03610926.2023.2282380Communications in Statistics - Theory and Methods2023-11-28T07:03:31ZXia HanDanping LiYu Yuana School of Mathematical Sciences and LPMC, Nankai University, Tianjin, Chinab Key Laboratory of Advanced Theory and Application in Statistics and Data Science- MOE, School of Statistics, Faculty of Economics and Management, East China Normal University, Shanghai, Chinac School of Management Science and Engineering, Nanjing University of Information Science and Technology, Jiangsu, ChinaCommunications in Statistics - Theory and Methods14510.1080/03610926.2023.2282380https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2282380?af=RParameter estimation for fractional power type diffusion: A hybrid Bayesian-deep learning approach
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. <br/>. <br/>Parameter estimation for fractional power type diffusion: A hybrid Bayesian-deep learning approachdoi:10.1080/03610926.2023.2280522Communications in Statistics - Theory and Methods2023-11-28T09:23:16ZHéctor ArayaFrancisco Plaza-Vegaa Facultad de Ingeniería y Ciencias, Universidad Adolfo Ibán∼ez, Chileb Universidad de Santiago de Chile, ChileCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2280522https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2280522?af=ROptimal choice of IHS-type of transformations for log-linear modeling
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. <br/>. <br/>Optimal choice of IHS-type of transformations for log-linear modelingdoi:10.1080/03610926.2023.2277671Communications in Statistics - Theory and Methods2023-11-30T02:22:22ZWolfgang M. GrimmIndependent Research and Consulting, Leonberg, GermanyCommunications in Statistics - Theory and Methods12910.1080/03610926.2023.2277671https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2277671?af=RAsymptotic normality for the wavelet partially linear additive model components estimation
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. <br/>. <br/>Asymptotic normality for the wavelet partially linear additive model components estimationdoi:10.1080/03610926.2023.2286905Communications in Statistics - Theory and Methods2023-12-01T06:36:51ZKhalid ChokriSalim Bouzebdaa Modeling and Complex Systems Laboratory-M.C.S.L., Cadi Ayyad University, Marrakech, Moroccob Laboratoire de Mathématiques Appliquées de Compiègne-L.M.A.C., Université de Technologie de Compiègne, Compiègne cedex, FranceCommunications in Statistics - Theory and Methods13610.1080/03610926.2023.2286905https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2286905?af=RBayesian Φq-optimal designs for multi-factor additive non linear models with heteroscedastic errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2288805?af=R
. <br/>. <br/>Bayesian Φq-optimal designs for multi-factor additive non linear models with heteroscedastic errorsdoi:10.1080/03610926.2023.2288805Communications in Statistics - Theory and Methods2023-12-05T01:13:11ZWei LengJuliang YinSchool of Economics and Statistics, Guangzhou University, Guangzhou, ChinaCommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2288805https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2288805?af=RExact convergence rate in central limit theorem for a supercritical branching process with immigration in a random environment
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. <br/>. <br/>Exact convergence rate in central limit theorem for a supercritical branching process with immigration in a random environmentdoi:10.1080/03610926.2023.2288792Communications in Statistics - Theory and Methods2023-12-09T11:14:07ZYingqiu LiXinping TangHesong WangSchool of Mathematics and Statistics, Changsha University of Science and Technology, Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering, Changsha, Hunan, PR ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2288792https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2288792?af=RHuber-Dutter estimation of linear models with dependent errors
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. <br/>. <br/>Huber-Dutter estimation of linear models with dependent errorsdoi:10.1080/03610926.2023.2290980Communications in Statistics - Theory and Methods2023-12-09T11:31:59ZZhen ZengFeng Xua School of Applied Mathematics, Nanjing University of Finance and Economics, Nanjing, PR Chinab College of Science, Guilin University of Technology, Guilin, PR ChinaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2290980https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2290980?af=RStatistical inference for the step-stress model with competing risks from the Kumaraswamy distribution under progressive type-II censoring
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. <br/>. <br/>Statistical inference for the step-stress model with competing risks from the Kumaraswamy distribution under progressive type-II censoringdoi:10.1080/03610926.2023.2291342Communications in Statistics - Theory and Methods2023-12-14T05:40:23ZXinjing WangTianrui YeWenhao Guia School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, Chinab Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, North Carolina, USACommunications in Statistics - Theory and Methods12810.1080/03610926.2023.2291342https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2291342?af=ROn the construction of asymmetric third-order rotatable designs
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. <br/>. <br/>On the construction of asymmetric third-order rotatable designsdoi:10.1080/03610926.2023.2281891Communications in Statistics - Theory and Methods2023-11-28T05:50:20ZAnkita VermaSeema JaggiEldho VargheseArpan BhowmikCini VargheseAnindita Dattaa ICAR-Indian Agricultural Statistics Research Institute, New Delhi, Indiab Agricultural Education Division, ICAR, New Delhi, Indiac ICAR-Central Marine Fisheries Research Institute, Kochi, Indiad ICAR-Indian Agricultural Research Institute, Assam, IndiaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2281891https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281891?af=REstimating the scale parameters of several exponential distributions under order restriction
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. <br/>. <br/>Estimating the scale parameters of several exponential distributions under order restrictiondoi:10.1080/03610926.2023.2292967Communications in Statistics - Theory and Methods2023-12-15T02:41:27ZSuchandan KayalLakshmi Kanta Patraa Department of Mathematics, National Institute of Technology Rourkela, Roukela, Indiab Department of Mathematics, Indian Institute of Technology Bhilai, Durg, IndiaCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2292967https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2292967?af=RPhase-type stress-strength reliability models under progressive type-II right censoring
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. <br/>. <br/>Phase-type stress-strength reliability models under progressive type-II right censoringdoi:10.1080/03610926.2023.2292968Communications in Statistics - Theory and Methods2023-12-15T03:19:44ZJoby K. JoseDrisya MKulathinal SangitaSebastian Georgea Department of Statistical Sciences, Kannur University, Kerala, Indiab Department of Statistics, Government Victoria College, Palakkad, Kerala, Indiac Department of Mathematics and Statistics, University of Helsinki, Helsinki, FinlandCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2292968https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2292968?af=RA generalized Rényi entropy to measure the uncertainty of a random permutation set
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. <br/>. <br/>A generalized Rényi entropy to measure the uncertainty of a random permutation setdoi:10.1080/03610926.2023.2292973Communications in Statistics - Theory and Methods2023-12-20T08:25:23ZBingguang HaoYuelin CheLuyuan ChenYong Denga Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, Chinab Yingcai Honors College, University of Electronic Science and Technology of China, Chengdu, Chinac School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, Chinad School of Medicine, Vanderbilt University, Nashville, Tennessee, USACommunications in Statistics - Theory and Methods11310.1080/03610926.2023.2292973https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2292973?af=RTests in functional autoregressive processes via local asymptotic normality condition
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. <br/>. <br/>Tests in functional autoregressive processes via local asymptotic normality conditiondoi:10.1080/03610926.2023.2293641Communications in Statistics - Theory and Methods2023-12-20T08:29:56ZKara-Terki NesrineHigher School of Management-Tlemcen, Random Statistics and Modeling Laboratory, University of Abou Bakr Belkaid, Tlemcen, AlgeriaCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2293641https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2293641?af=RAsymptotics for a bidimensional delay-claim risk model with subexponential claims and arbitrary dependence between the generic inter-arrival time pair
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. <br/>. <br/>Asymptotics for a bidimensional delay-claim risk model with subexponential claims and arbitrary dependence between the generic inter-arrival time pairdoi:10.1080/03610926.2023.2293642Communications in Statistics - Theory and Methods2023-12-22T08:01:29ZKeya ZhangShijie WangSchool of Big Data and Statistics, Anhui University, Hefei, Anhui, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2293642https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2293642?af=RThe estimations of drift parameters for the Gaussian Vasicek process with time-varying volatility
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. <br/>. <br/>The estimations of drift parameters for the Gaussian Vasicek process with time-varying volatilitydoi:10.1080/03610926.2023.2293650Communications in Statistics - Theory and Methods2023-12-22T08:27:28ZJixia WangLu SunYu MiaoCollege of Mathematics and Information Science, Henan Normal University, Henan Province, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2293650https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2293650?af=ROptimal investment and benefit payment adjustment strategies for the target benefit plan under partial information
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. <br/>. <br/>Optimal investment and benefit payment adjustment strategies for the target benefit plan under partial informationdoi:10.1080/03610926.2023.2295587Communications in Statistics - Theory and Methods2023-12-28T10:03:55ZWanjin ChenXingchun PengSchool of Science, Wuhan University of Technology, Wuhan, PR ChinaCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2295587https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2295587?af=RNon parametric deconvolution of cumulative distribution function from repeated observations with unknown noise distribution
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. <br/>. <br/>Non parametric deconvolution of cumulative distribution function from repeated observations with unknown noise distributiondoi:10.1080/03610926.2023.2298896Communications in Statistics - Theory and Methods2023-12-29T05:37:16ZBui Thuy TrangLe Thi Hong ThuyCao Xuan Phuonga Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnamb Faculty of Fundamental Sciences, Van Lang University, Ho Chi Minh City, VietnamCommunications in Statistics - Theory and Methods13210.1080/03610926.2023.2298896https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2298896?af=RAlmost sure asymptotic representation for the conditional copula estimator
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. <br/>. <br/>Almost sure asymptotic representation for the conditional copula estimatordoi:10.1080/03610926.2023.2300318Communications in Statistics - Theory and Methods2024-01-03T02:06:46ZNoël VeraverbekeUniversiteit Hasselt, Belgium and North-West University, South AfricaCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2300318https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2300318?af=RA mixed INAR(p) model with serially dependent innovation with application to some COVID-19 data
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. <br/>. <br/>A mixed INAR(p) model with serially dependent innovation with application to some COVID-19 datadoi:10.1080/03610926.2023.2300305Communications in Statistics - Theory and Methods2024-01-04T12:11:17ZXiufang LiuWenzheng YinWenkun ZhangHuaping Chena School of Mathematics, Taiyuan University of Technology, Taiyuan, PR Chinab School of Mathematics and Statistics, Henan University, Kaifeng, PR ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2023.2300305https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2300305?af=RMultiple imputation in the functional linear model with partially observed covariate and missing values in the response
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. <br/>. <br/>Multiple imputation in the functional linear model with partially observed covariate and missing values in the responsedoi:10.1080/03610926.2023.2300312Communications in Statistics - Theory and Methods2024-01-08T10:05:40ZChristophe CrambesChayma DaayebAli GannounYousri Henchiria Institut Montpelliérain Alexander Grothendieck (IMAG), Université de Montpellier, Franceb Université de Tunis El Manar, Laboratoire de Modélisation Mathématique et Numérique dans les Sciences de l’Ingénieur (LAMSIN) Tunis, Tunisiec Université de la Manouba, Institut Supérieur des Arts Multimédia de la Manouba (ISAMM), TunisieCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2300312https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2300312?af=RA stratified modified probability proportional to size sampling technique
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2292969?af=R
. <br/>. <br/>A stratified modified probability proportional to size sampling techniquedoi:10.1080/03610926.2023.2292969Communications in Statistics - Theory and Methods2024-01-08T05:52:01ZAnupama GoyalSangeeta AroraAnju GoyalDepartment of Statistics, Panjab University, Chandigarh, IndiaCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2292969https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2292969?af=RExistence of schematic arrays under a novel criterion
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. <br/>. <br/>Existence of schematic arrays under a novel criteriondoi:10.1080/03610926.2024.2301979Communications in Statistics - Theory and Methods2024-01-10T01:19:34ZZuolu HaoYu TangSchool of Mathematical Sciences, Soochow University, Suzhou, ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2024.2301979https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2301979?af=RConstruction of two-level component orthogonal arrays for order-of-addition experiments
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. <br/>. <br/>Construction of two-level component orthogonal arrays for order-of-addition experimentsdoi:10.1080/03610926.2024.2301978Communications in Statistics - Theory and Methods2024-01-12T03:27:47ZGuangni MoYuyao WangShuhao WeiJin LiHengzhen HuangXueru Zhanga College of Mathematics and Statistics, Guangxi Normal University, Guilin, Chinab Department of Statistics, Purdue University, West Lafayette, IN, USACommunications in Statistics - Theory and Methods1910.1080/03610926.2024.2301978https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2301978?af=RConstruction of efficient classes of circular balanced repeated measurements designs with R
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2300307?af=R
. <br/>. <br/>Construction of efficient classes of circular balanced repeated measurements designs with Rdoi:10.1080/03610926.2023.2300307Communications in Statistics - Theory and Methods2024-01-13T05:02:30ZMuhammad RiazMahmood Ul HassanM. H. TahirH. M. Kashif RasheedAbid KhanRashid Ahmeda Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Pakistanb Department of Statistics, Stockholm University, Stockholm, SwedenCommunications in Statistics - Theory and Methods11510.1080/03610926.2023.2300307https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2300307?af=ROn the scaled Rényi entropy and application
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. <br/>. <br/>On the scaled Rényi entropy and applicationdoi:10.1080/03610926.2024.2301986Communications in Statistics - Theory and Methods2024-01-16T12:45:05ZPengyue YuYong Denga Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, Chinab Glasgow College, University of Electronic Science and Technology of China, Chengdu, Chinac School of Medicine, Vanderbilt University, Nashville, Tennessee, USACommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2301986https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2301986?af=RBerry-Esseen’s bound for a superadditive bisexual branching process in a random environment
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. <br/>. <br/>Berry-Esseen’s bound for a superadditive bisexual branching process in a random environmentdoi:10.1080/03610926.2024.2301991Communications in Statistics - Theory and Methods2024-01-19T01:31:03ZSheng XiaoXiangdong LiuDepartment of Statistics, Jinan University, Guangzhou Guangdong, PR ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2301991https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2301991?af=RPrediction and estimation of random variables with infinite mean or variance
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2303976?af=R
. <br/>. <br/>Prediction and estimation of random variables with infinite mean or variancedoi:10.1080/03610926.2024.2303976Communications in Statistics - Theory and Methods2024-01-19T01:50:14ZVictor de la PeñaHenryk GzylSilvia MayoralHaolin ZouDemissie Alemayehua Department of Statistics, Columbia University, New York, New York, USAb Center for Finance, IESA, Caracas, Venezuelac Department of Business Administration, Universidad Carlos III de Madrid, Madrid, Spain.d Pfizer Inc, New York, New York, USACommunications in Statistics - Theory and Methods11510.1080/03610926.2024.2303976https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2303976?af=ROne component partial least squares, high dimensional regression, data splitting, and the multitude of models
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2303979?af=R
. <br/>. <br/>One component partial least squares, high dimensional regression, data splitting, and the multitude of modelsdoi:10.1080/03610926.2024.2303979Communications in Statistics - Theory and Methods2024-01-22T11:38:11ZDavid J. OliveLingling Zhanga School of Mathematical & Statistical Sciences, Southern Illinois University, Carbondale, Illinois, USAb Department of Mathematics, University at Albany, Albany, New York, USACommunications in Statistics - Theory and Methods11710.1080/03610926.2024.2303979https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2303979?af=RRegression with continuous mixture of Gaussian distributions for modeling the memory time of water treatment
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2303992?af=R
. <br/>. <br/>Regression with continuous mixture of Gaussian distributions for modeling the memory time of water treatmentdoi:10.1080/03610926.2024.2303992Communications in Statistics - Theory and Methods2024-01-22T03:28:04ZNahla Ben Salaha Laboratory of Probability and Statistics, Faculty of Sciences Sfax, Sfax University, Sfax, Tunisiab Higher Institute of Environmental Sciences and Technologies, Carthage University, Tunis, TunisiaCommunications in Statistics - Theory and Methods11310.1080/03610926.2024.2303992https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2303992?af=RAn evolving pseudofractal network model
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2306524?af=R
. <br/>. <br/>An evolving pseudofractal network modeldoi:10.1080/03610926.2024.2306524Communications in Statistics - Theory and Methods2024-01-23T06:15:51ZXing LiQunqiang FengClearance AbelAo Shena Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Chinab Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BotswanaCommunications in Statistics - Theory and Methods11310.1080/03610926.2024.2306524https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2306524?af=RSome results on characterization of distributions in reliability analysis
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2306543?af=R
. <br/>. <br/>Some results on characterization of distributions in reliability analysisdoi:10.1080/03610926.2024.2306543Communications in Statistics - Theory and Methods2024-01-27T12:13:19ZSubarna BhattacharjeeRajib Lochan GiriMagdalena Szymkowiaka Department of Mathematics, Ravenshaw University, Cuttack, Odisha, Indiab Institute of Automatic Control and Robotics, Poznan University of Technology, Poznań, PolandCommunications in Statistics - Theory and Methods11210.1080/03610926.2024.2306543https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2306543?af=ROn relationships between Chatterjee’s and Spearman’s correlation coefficients
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309971?af=R
. <br/>. <br/>On relationships between Chatterjee’s and Spearman’s correlation coefficientsdoi:10.1080/03610926.2024.2309971Communications in Statistics - Theory and Methods2024-02-01T07:12:30ZQingyang ZhangDepartment of Mathematical Sciences, University of Arkansas, Fayetteville, Arkansas, USACommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2309971https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309971?af=RA flexible extension of asymmetric power-t distribution
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2306520?af=R
. <br/>. <br/>A flexible extension of asymmetric power-t distributiondoi:10.1080/03610926.2024.2306520Communications in Statistics - Theory and Methods2024-02-02T11:29:34ZHuifang YuanTao Jianga School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, Zhejiang, Chinab School of Mathematics and Statistics, Zaozhaung University, Zaozhaung, Shandong, Chinac Zhejiang Gongshang University Hangzhou College of Commerce, Zaozhuang, Shandong, ChinaCommunications in Statistics - Theory and Methods13210.1080/03610926.2024.2306520https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2306520?af=REvaluation of the number of clusters in a data set using p-values from multiple tests of hypotheses
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. <br/>. <br/>Evaluation of the number of clusters in a data set using p-values from multiple tests of hypothesesdoi:10.1080/03610926.2024.2309967Communications in Statistics - Theory and Methods2024-02-03T09:31:24ZDr. Soumita ModakFaculty, Department of Statistics, University of Calcutta, Basanti Devi College, Kolkata, IndiaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2309967https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309967?af=RA longitudinal complex likelihood ratio test for pleiotropy
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309979?af=R
. <br/>. <br/>A longitudinal complex likelihood ratio test for pleiotropydoi:10.1080/03610926.2024.2309979Communications in Statistics - Theory and Methods2024-02-04T10:43:29ZQiang WuXingwei TongJianguo SunMeng Lia School of Statistics, Beijing Normal University, Beijing, Chinab Department of Statistics, University of Missouri, Columbia, Missouri, USACommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2309979https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309979?af=RParameter estimation for Gegenbaeur Arfisma processes with infinite variance innovations
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2307453?af=R
. <br/>. <br/>Parameter estimation for Gegenbaeur Arfisma processes with infinite variance innovationsdoi:10.1080/03610926.2024.2307453Communications in Statistics - Theory and Methods2024-02-06T01:10:43ZFilamory Abraham Michael KeïtaOuagnina HiliSerge-Hippolyte Arnaud KangaUMRI Mathématique et Nouvelles Technologies de l’Information, Institut National Polytechnique Felix Houphouët-Boigny, Yamoussoukro, Côte d’IvoireCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2307453https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2307453?af=RSurvival tree averaging by functional martingale-based residuals
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309980?af=R
. <br/>. <br/>Survival tree averaging by functional martingale-based residualsdoi:10.1080/03610926.2024.2309980Communications in Statistics - Theory and Methods2024-02-06T03:12:00ZChang WangBaihua HeShishun ZhaoJianguo SunXinyu Zhanga Center for Applied Statistical Research and College of Mathematics, Jilin University, Changchun, Chinab School of Management, University of Science and Technology of China, Hefei, Chinac Department of Statistics, University of Missouri, Columbia, Missouri, USAd Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, ChinaCommunications in Statistics - Theory and Methods12710.1080/03610926.2024.2309980https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309980?af=RSup-extropy: A measure of uncertainty
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. <br/>. <br/>Sup-extropy: A measure of uncertaintydoi:10.1080/03610926.2024.2309984Communications in Statistics - Theory and Methods2024-02-07T10:51:05ZHusam A. BayoudMohammad Z. Raqaba College of Sciences and Humanities, Fahad Bin Sultan University, Tabuk, Saudi Arabiab Department of Statistics & Operations Research, Kuwait University, Al-Shadadiyya, KuwaitCommunications in Statistics - Theory and Methods11410.1080/03610926.2024.2309984https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309984?af=RMoment-type estimation for Type-I censored samples
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2310698?af=R
. <br/>. <br/>Moment-type estimation for Type-I censored samplesdoi:10.1080/03610926.2024.2310698Communications in Statistics - Theory and Methods2024-02-09T10:37:14ZPiotr Bolesław NowakInstitute of Economic Sciences, University of Wrocław Faculty of Law, Administration and Economics, Wrocław, PolandCommunications in Statistics - Theory and Methods11210.1080/03610926.2024.2310698https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2310698?af=RCluster-weighted modeling with measurement error in covariates
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2311795?af=R
. <br/>. <br/>Cluster-weighted modeling with measurement error in covariatesdoi:10.1080/03610926.2024.2311795Communications in Statistics - Theory and Methods2024-02-09T10:43:03ZShaho ZareiDepartment of Statistics, Faculty of Science, University of Kurdistan, Sanandaj, IranCommunications in Statistics - Theory and Methods11310.1080/03610926.2024.2311795https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2311795?af=RA study on utilization of two cold standby components to increase reliability of a coherent system
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309981?af=R
. <br/>. <br/>A study on utilization of two cold standby components to increase reliability of a coherent systemdoi:10.1080/03610926.2024.2309981Communications in Statistics - Theory and Methods2024-02-15T11:50:41ZAchintya RoyNitin Guptaa Department of Mathematics, Indian Institute of Technology, Kharagpur, West Bengal, Indiab Department of Mathematics and Basic Sciences, NIIT University, Neemrana, Rajasthan, IndiaCommunications in Statistics - Theory and Methods12810.1080/03610926.2024.2309981https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2309981?af=RVariation of conditional mean and its application in ultrahigh dimensional feature screening
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2310690?af=R
. <br/>. <br/>Variation of conditional mean and its application in ultrahigh dimensional feature screeningdoi:10.1080/03610926.2024.2310690Communications in Statistics - Theory and Methods2024-02-15T11:57:44ZZhentao TianTingyu LaiZhongzhan Zhanga Beijing University of Technology, Beijing, Chinab Guangxi Normal University, Guilin, ChinaCommunications in Statistics - Theory and Methods13110.1080/03610926.2024.2310690https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2310690?af=RModeling the association of bivariate interval-censored data under the additive hazards model
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2310691?af=R
. <br/>. <br/>Modeling the association of bivariate interval-censored data under the additive hazards modeldoi:10.1080/03610926.2024.2310691Communications in Statistics - Theory and Methods2024-02-15T11:59:55ZLing ChenLei LiuYanqin FengJianguo SunShu Jianga Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USAb School of Mathematics and Statistics, Wuhan University, Wuhan Chinac Department of Statistics, University of Missouri, Columbia, Missouri, USA.d Division of Public Health Sciences, Washington University School of Medicine, St. Louis, Missouri, USACommunications in Statistics - Theory and Methods11310.1080/03610926.2024.2310691https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2310691?af=RA switcher skip lot-sampling plan under resubmitted lots using the Taguchi capability index for building a solid vendor-customer relationship
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2314621?af=R
. <br/>. <br/>A switcher skip lot-sampling plan under resubmitted lots using the Taguchi capability index for building a solid vendor-customer relationshipdoi:10.1080/03610926.2024.2314621Communications in Statistics - Theory and Methods2024-02-15T12:17:55ZNabil El FarmeEmines – School Of Industrial Management, Mohammed VI Polytechnic University, Ben Guerir, MoroccoCommunications in Statistics - Theory and Methods12410.1080/03610926.2024.2314621https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2314621?af=RAsymptotics in the Bradley-Terry model for networks with a differentially private degree sequence
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2313063?af=R
. <br/>. <br/>Asymptotics in the Bradley-Terry model for networks with a differentially private degree sequencedoi:10.1080/03610926.2024.2313063Communications in Statistics - Theory and Methods2024-02-16T01:27:52ZYang OuyangLuo JingWang QiupingXu Zhimenga National Institute of Cultural Development, Wuhan University, Wuhan, Chinab Department of Mathematics and Statistics, South-Central Minzu University, Wuhan, Chinac School of Mathematics and Statistics and Key Laboratory of Nonlinear Analysis and Applications (Ministry of Education), Central China Normal University, Wuhan, Chinad School of Mathematics and Statistics, Zhaoqing University, Zhaoqing, China.Communications in Statistics - Theory and Methods12010.1080/03610926.2024.2313063https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2313063?af=RA form of bivariate binomial conditionals distributions
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315294?af=R
. <br/>. <br/>A form of bivariate binomial conditionals distributionsdoi:10.1080/03610926.2024.2315294Communications in Statistics - Theory and Methods2024-02-19T11:56:58ZIndranil GhoshFilipe MarquesSubrata Chakrabortya University of North Carolina, Wilmington, North Carolina, USAb Universidade Nova de Lisboa, Lisbon, Portugalc Dibrugarh University, Dibrugarh, Assam, IndiaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2315294https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315294?af=ROn integer partitions and the Wilcoxon rank-sum statistic
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315297?af=R
. <br/>. <br/>On integer partitions and the Wilcoxon rank-sum statisticdoi:10.1080/03610926.2024.2315297Communications in Statistics - Theory and Methods2024-02-19T12:02:17ZAndrew V. SillsDepartment of Mathematical Sciences, Georgia Southern University, Statesboro and Savannah, Georgia, USACommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2315297https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315297?af=RA nonparametric test for homogeneity of variances
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316274?af=R
. <br/>. <br/>A nonparametric test for homogeneity of variancesdoi:10.1080/03610926.2024.2316274Communications in Statistics - Theory and Methods2024-02-20T12:02:21ZJ.A. Villase∼norE. González-EstradaDepartment of Statistics, Colegio de Postgraduados, MexicoCommunications in Statistics - Theory and Methods1910.1080/03610926.2024.2316274https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316274?af=ROptimal asset allocation for DC pension subject to allocation and terminal wealth constraints under a remuneration scheme
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. <br/>. <br/>Optimal asset allocation for DC pension subject to allocation and terminal wealth constraints under a remuneration schemedoi:10.1080/03610926.2024.2316282Communications in Statistics - Theory and Methods2024-02-20T12:08:32ZYinghui DongMengyuan ShiChunrong Huaa School of Math and Physics, Suzhou University of Science and Technology, Suzhou, P. R. Chinab Department of Mathematics and Statistics, Changshu Institute of Technology, Changshu, P. R. ChinaCommunications in Statistics - Theory and Methods12810.1080/03610926.2024.2316282https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316282?af=RComplete convergence for weighted sums of widely negative orthant dependent random variables under the sub-linear expectations
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2307454?af=R
. <br/>. <br/>Complete convergence for weighted sums of widely negative orthant dependent random variables under the sub-linear expectationsdoi:10.1080/03610926.2024.2307454Communications in Statistics - Theory and Methods2024-02-21T10:56:28ZLizhen HuangQunying WuCollege of Science, Guilin University of Technology, Guilin, PR ChinaCommunications in Statistics - Theory and Methods11210.1080/03610926.2024.2307454https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2307454?af=RComparison of predictors under constrained general linear model and its future observations
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2314618?af=R
. <br/>. <br/>Comparison of predictors under constrained general linear model and its future observationsdoi:10.1080/03610926.2024.2314618Communications in Statistics - Theory and Methods2024-02-21T11:04:58ZMelek Eriş BüyükkayaDepartment of Statistics and Computer Sciences, Karadeniz Technical University, Trabzon, TurkeyCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2314618https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2314618?af=REvaluating cyber loss in star-ring and star-bus hybrid networks based on the bond percolation model
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. <br/>. <br/>Evaluating cyber loss in star-ring and star-bus hybrid networks based on the bond percolation modeldoi:10.1080/03610926.2024.2315291Communications in Statistics - Theory and Methods2024-02-21T11:13:24ZGaofeng DaZhexuan RenCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, ChinaCommunications in Statistics - Theory and Methods13410.1080/03610926.2024.2315291https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315291?af=ROn the rate of asymptotic normality of integral weighted kernel estimator in a non parametric regression model for φ-mixing random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316261?af=R
. <br/>. <br/>On the rate of asymptotic normality of integral weighted kernel estimator in a non parametric regression model for φ-mixing random variablesdoi:10.1080/03610926.2024.2316261Communications in Statistics - Theory and Methods2024-02-21T11:12:40ZLiwang DingCaoqing Jianga School of Mathematics and Quantitative Economics, Guangxi University of Finance and Economics, Nanning, Chinab School of Big Data and Artificial Intelligence, Guangxi University of Finance and Economics, Nanning, ChinaCommunications in Statistics - Theory and Methods11610.1080/03610926.2024.2316261https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316261?af=ROn a novel skewed generalized t distribution: Properties, estimations, and its applications
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2313034?af=R
. <br/>. <br/>On a novel skewed generalized t distribution: Properties, estimations, and its applicationsdoi:10.1080/03610926.2024.2313034Communications in Statistics - Theory and Methods2024-02-22T05:30:22ZChengdi LianYaohua RongWeihu ChengFaculty of Science, Beijing University of Technology, Beijing, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2024.2313034https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2313034?af=ROptimal investment problem for a hybrid pension with intergenerational risk-sharing and longevity trend under model uncertainty
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315295?af=R
. <br/>. <br/>Optimal investment problem for a hybrid pension with intergenerational risk-sharing and longevity trend under model uncertaintydoi:10.1080/03610926.2024.2315295Communications in Statistics - Theory and Methods2024-02-23T07:39:48ZKe FuXimin RongHui Zhaoa School of Mathematics, Tianjin University, Tianjin, P.R. Chinab Center for Applied Mathematics, Tianjin University, Tianjin, P.R. ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2024.2315295https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315295?af=RSaddlepoint approximations for the P-values and probability mass functions of some bivariate sign tests
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315293?af=R
. <br/>. <br/>Saddlepoint approximations for the P-values and probability mass functions of some bivariate sign testsdoi:10.1080/03610926.2024.2315293Communications in Statistics - Theory and Methods2024-02-24T04:55:53ZAbd El-Raheem M. Abd El-RaheemIbrahim A. A. ShananEhab F. Abd-Elfattaha Department of Mathematics, Faculty of Education, Ain Shams University, Cairo, Egyptb Department of Information Technologies, Management Technical College, Southern Technical University, Basra, IraqCommunications in Statistics - Theory and Methods11210.1080/03610926.2024.2315293https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315293?af=RA Bayesian robustness measure in significance tests for equivalence tests
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316275?af=R
. <br/>. <br/>A Bayesian robustness measure in significance tests for equivalence testsdoi:10.1080/03610926.2024.2316275Communications in Statistics - Theory and Methods2024-02-24T05:17:00ZJosimara Tatiane da SilvaMário de Castroa Universidade de S∼ao Paulo, Instituto de Ciências Matemáticas e de Computaç∼ao, S∼ao Carlos, S∼ao Paulo, Brazilb Statistics Department, Federal University of S∼ao Carlos, S∼ao Carlos, S∼ao Paulo, BrazilCommunications in Statistics - Theory and Methods11810.1080/03610926.2024.2316275https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316275?af=RJajte-type strong limit theorem for pairwise negatively quadrant dependent random variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2319094?af=R
. <br/>. <br/>Jajte-type strong limit theorem for pairwise negatively quadrant dependent random variablesdoi:10.1080/03610926.2024.2319094Communications in Statistics - Theory and Methods2024-02-24T05:19:38ZYongfeng WuTien-Chung Hua School of Mathematics and Computer Science, Tongling University, Anhui, Tongling, Chinab School of Mathematics and Finance, Chuzhou University, Anhui, Chuzhou, Chinac Department of Mathematics, National Tsing Hua University, Hsinchu, Taiwan, ROCCommunications in Statistics - Theory and Methods11010.1080/03610926.2024.2319094https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2319094?af=RStandby redundancy allocation for series and parallel systems
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316270?af=R
. <br/>. <br/>Standby redundancy allocation for series and parallel systemsdoi:10.1080/03610926.2024.2316270Communications in Statistics - Theory and Methods2024-02-26T12:23:21ZRavi KumarSameen NaqviDepartment of Mathematics, Indian Institute of Technology Hyderabad, Hyderabad, India.Communications in Statistics - Theory and Methods12410.1080/03610926.2024.2316270https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2316270?af=RTuning up the Kolmogorov–Smirnov test for testing Benford’s law
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2318608?af=R
. <br/>. <br/>Tuning up the Kolmogorov–Smirnov test for testing Benford’s lawdoi:10.1080/03610926.2024.2318608Communications in Statistics - Theory and Methods2024-02-29T06:46:41ZLeonardo CampanelliSchool of Medicine, All Saints University, Toronto, Ontario, CanadaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2318608https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2318608?af=RAsymptotics for the ruin probability in a proportional reinsurance risk model with dependent insurance and financial risks
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. <br/>. <br/>Asymptotics for the ruin probability in a proportional reinsurance risk model with dependent insurance and financial risksdoi:10.1080/03610926.2024.2318606Communications in Statistics - Theory and Methods2024-02-29T02:27:40ZMing ChengDingcheng WangSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2318606https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2318606?af=RComplete convergence for arrays of rowwise mn-extended negatively dependent random variables and its application
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2321172?af=R
. <br/>. <br/>Complete convergence for arrays of rowwise mn-extended negatively dependent random variables and its applicationdoi:10.1080/03610926.2024.2321172Communications in Statistics - Theory and Methods2024-02-29T02:53:04ZJinyu ZhouZongfeng QiJigao Yana State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE), Luoyang, Chinab School of Mathematical Sciences, Soochow University, Suzhou, ChinaCommunications in Statistics - Theory and Methods11710.1080/03610926.2024.2321172https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2321172?af=ROn impurity functions in decision trees
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2317359?af=R
. <br/>. <br/>On impurity functions in decision treesdoi:10.1080/03610926.2024.2317359Communications in Statistics - Theory and Methods2024-03-04T10:40:25ZGuoping ZengIndependent Researcher, Plano, TX, USACommunications in Statistics - Theory and Methods11910.1080/03610926.2024.2317359https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2317359?af=RA note on estimating multivariate Gaussian mixtures with unknown number of components
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. <br/>. <br/>A note on estimating multivariate Gaussian mixtures with unknown number of componentsdoi:10.1080/03610926.2024.2321498Communications in Statistics - Theory and Methods2024-03-06T09:51:28ZYingwei Zhoua School of Statistics and Management, Shanghai University of Finance, and Economics, Shanghai, P. R. ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2321498https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2321498?af=RPosterior contraction rates for constrained deep Gaussian processes in density estimation and classification
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. <br/>. <br/>Posterior contraction rates for constrained deep Gaussian processes in density estimation and classificationdoi:10.1080/03610926.2024.2321185Communications in Statistics - Theory and Methods2024-03-07T02:42:43ZFrançois BachocAgnès LagnouxInstitut de Mathématiques de Toulouse, Université de Toulouse, Toulouse, FranceCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2321185https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2321185?af=RA comparison of objective priors for Cronbach’s coefficient alpha using a balanced random effects model
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. <br/>. <br/>A comparison of objective priors for Cronbach’s coefficient alpha using a balanced random effects modeldoi:10.1080/03610926.2024.2315300Communications in Statistics - Theory and Methods2024-03-08T01:43:30ZSharkay R. IzallyAbraham J. van der MerweLizanne Raubenheimera Department of Statistics, Rhodes University, Makhanda, South Africab Department of Mathematical Statistics and Actuarial Science, University of the Free State, Bloemfontein, South AfricaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2315300https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2315300?af=RAn alternative multivariate exponential power distribution
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2321506?af=R
. <br/>. <br/>An alternative multivariate exponential power distributiondoi:10.1080/03610926.2024.2321506Communications in Statistics - Theory and Methods2024-03-11T04:33:01ZMichael ManfordBismark Kwao NkansahHenrietta NkansahArimiyaw Zakariaa Department of Mathematics and Statistics, Cape Coast Technical University, Cape Coast, Ghanab Department of Statistics, University of Cape Coast, Cape Coast, Ghanac Department of Mathematics, University of Cape Coast, Cape Coast, GhanaCommunications in Statistics - Theory and Methods11910.1080/03610926.2024.2321506https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2321506?af=ROn the variance estimator and its bounds in general linear models under linear restrictions
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328162?af=R
. <br/>. <br/>On the variance estimator and its bounds in general linear models under linear restrictionsdoi:10.1080/03610926.2024.2328162Communications in Statistics - Theory and Methods2024-03-14T07:07:48ZZaixing LiChanglei LiuMenghan Yia Department of Mathematics, China University of Mining and Technology-Beijing, Beijing, Chinab School of Statistics, East China Normal University, Shanghai, ChinaCommunications in Statistics - Theory and Methods11110.1080/03610926.2024.2328162https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328162?af=RA note on sharp oracle bounds for Slope and Lasso
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. <br/>. <br/>A note on sharp oracle bounds for Slope and Lassodoi:10.1080/03610926.2024.2328165Communications in Statistics - Theory and Methods2024-03-18T12:31:11ZZhiyong ZhouDepartment of Statistics and Data Science, and Institute of Digital Finance, Hangzhou City University, Hangzhou, China.Communications in Statistics - Theory and Methods11910.1080/03610926.2024.2328165https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328165?af=RConvergence of extremes from normal-skew-normal and minima and maxima from exchangeable trivariate normal distributions
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. <br/>. <br/>Convergence of extremes from normal-skew-normal and minima and maxima from exchangeable trivariate normal distributionsdoi:10.1080/03610926.2024.2328170Communications in Statistics - Theory and Methods2024-03-18T12:35:10ZMehdi AmiriAsma TeimouriMohsen KhosraviAhad Jamalizadeha Department of Statistics, Faculty of Basic Sciences, University of Hormozgan, Bandarabbas, Iranb Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, IranCommunications in Statistics - Theory and Methods12110.1080/03610926.2024.2328170https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328170?af=RStatistical inference for the extended non linear models
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328174?af=R
. <br/>. <br/>Statistical inference for the extended non linear modelsdoi:10.1080/03610926.2024.2328174Communications in Statistics - Theory and Methods2024-03-18T12:38:31ZYang ZhaoYurui JieXiaofen WuDepartment of Mathematics, School of Mathematics and Computer Sciences, Nanchang University, Nanchang, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2024.2328174https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328174?af=RReinsurance, investment and the rationality with a diffusion model approximating a jump model
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. <br/>. <br/>Reinsurance, investment and the rationality with a diffusion model approximating a jump modeldoi:10.1080/03610926.2024.2328179Communications in Statistics - Theory and Methods2024-03-18T12:40:59ZDuni HuHailong Wanga School of Economics and Management, Nanchang University, Nanchang, P.R. Chinab Research Center of the Central China for Economic and Social Development, Nanchang University, Nanchang, P.R. ChinaCommunications in Statistics - Theory and Methods12310.1080/03610926.2024.2328179https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328179?af=RLocally, Bayesian and non parametric Bayesian optimal designs for unit exponential regression model
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328182?af=R
. <br/>. <br/>Locally, Bayesian and non parametric Bayesian optimal designs for unit exponential regression modeldoi:10.1080/03610926.2024.2328182Communications in Statistics - Theory and Methods2024-03-19T01:37:42ZAnita Abdollahi NanvapishehHabib JafariSoleiman KhazaeiDepartment of Statistics, Razi University, Kermanshah, IranCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2328182https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2328182?af=RA note on the covariate-dependent kink threshold regression model for panel data
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. <br/>. <br/>A note on the covariate-dependent kink threshold regression model for panel datadoi:10.1080/03610926.2024.2324985Communications in Statistics - Theory and Methods2024-03-23T06:32:20ZMaoyuan ZhouFangyu YeYi LiFengqi LiuChuang Wana School of Economics, Xiamen University, Xiamen, Chinab School of Economics and Management Changsha University, Changsha, Chinac College of Tourism, Hunan Normal University, Changsha, Chinad School of Economics, Nankai University, Tianjin, Chinae School of Statistics and Data Science, Nankai University, Tianjin, ChinaCommunications in Statistics - Theory and Methods1010.1080/03610926.2024.2324985https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2324985?af=RUnderstanding the alternative Mantel-Haenszel statistic: Factors affecting its robustness to detect non-uniform DIF
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. <br/>. <br/>Understanding the alternative Mantel-Haenszel statistic: Factors affecting its robustness to detect non-uniform DIFdoi:10.1080/03610926.2024.2330668Communications in Statistics - Theory and Methods2024-03-23T06:46:22ZMohammad MollazehiAbdel-Salam G. Abdel-Salama College of Arts and Sciences, Qatar University, Doha, Qatarb Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, QatarCommunications in Statistics - Theory and Methods12510.1080/03610926.2024.2330668https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2330668?af=RClosed testing procedure for comparing sizes of normal means based on ordered statistics
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329769?af=R
. <br/>. <br/>Closed testing procedure for comparing sizes of normal means based on ordered statisticsdoi:10.1080/03610926.2024.2329769Communications in Statistics - Theory and Methods2024-03-27T09:50:39ZT. ImadaDepartment of Human Information Engineering, Tokai University, Kumamoto, JapanCommunications in Statistics - Theory and Methods11010.1080/03610926.2024.2329769https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329769?af=RGibbs sampler for Bayesian prediction of triple seasonal autoregressive processes
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329780?af=R
. <br/>. <br/>Gibbs sampler for Bayesian prediction of triple seasonal autoregressive processesdoi:10.1080/03610926.2024.2329780Communications in Statistics - Theory and Methods2024-03-27T09:54:40ZAyman A. AminDepartment of Statistics, Mathematics, and Insurance, Faculty of Commerce, Menoufia University, Menoufia, Egypt.Communications in Statistics - Theory and Methods11910.1080/03610926.2024.2329780https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329780?af=RTwo-sample test for stochastic block models via the largest singular value
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. <br/>. <br/>Two-sample test for stochastic block models via the largest singular valuedoi:10.1080/03610926.2024.2330669Communications in Statistics - Theory and Methods2024-03-27T10:01:28ZKang FuJianwei HuSeydou KeitaHang Liua School of Mathematics and Statistics, Central China Normal University, Wuhan, Chinab Hubei Key Laboratory of Mathematical Sciences, Central China Normal University, Wuhan, Chinac Key Laboratory of Nonlinear Analysis and Applications (Ministry of Education), Central China Normal University, Wuhan, ChinaCommunications in Statistics - Theory and Methods12010.1080/03610926.2024.2330669https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2330669?af=RAn algebraic analysis of the bimodality of the generalized von Mises distribution
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. <br/>. <br/>An algebraic analysis of the bimodality of the generalized von Mises distributiondoi:10.1080/03610926.2022.2158345Communications in Statistics - Theory and Methods2022-12-23T05:39:48ZSara SalvadorRiccardo GattoInstitute of Mathematical Statistics and Actuarial Science Department of Mathematics and Statistics, University of Bern, Bern, SwitzerlandCommunications in Statistics - Theory and Methods11710.1080/03610926.2022.2158345https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2158345?af=RMonitoring the structure of social networks based on exponential random graph model
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. <br/>. <br/>Monitoring the structure of social networks based on exponential random graph modeldoi:10.1080/03610926.2022.2163366Communications in Statistics - Theory and Methods2023-01-03T08:59:53ZMahboubeh MohebbiAmirhossein AmiriAli Reza Taheriyouna Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iranb Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, IranCommunications in Statistics - Theory and Methods11610.1080/03610926.2022.2163366https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2163366?af=RD-optimal designs for two-variable logistic regression model with restricted design space
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. <br/>. <br/>D-optimal designs for two-variable logistic regression model with restricted design spacedoi:10.1080/03610926.2023.2167056Communications in Statistics - Theory and Methods2023-01-19T12:23:20ZYi ZhaiChengci WangHui-Yi LinZhide Fanga School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, Chinab Biostatistics Program, School of Public Health, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USACommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2167056https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2167056?af=RTwo-step conditional least squares estimation for the bivariate ℤ-valued INAR(1) model with bivariate Skellam innovations
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. <br/>. <br/>Two-step conditional least squares estimation for the bivariate ℤ-valued INAR(1) model with bivariate Skellam innovationsdoi:10.1080/03610926.2023.2172587Communications in Statistics - Theory and Methods2023-02-02T02:19:35ZHuaping ChenFukang ZhuXiufang Liua School of Mathematics and Statistics, Henan University, Kaifeng, Chinab School of Mathematics, Jilin University, Changchun, Chinac College of Mathematics, Taiyuan University of Technology, Taiyuan, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2172587https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2172587?af=REntropy of Random Permutation Set
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2173975?af=R
. <br/>. <br/>Entropy of Random Permutation Setdoi:10.1080/03610926.2023.2173975Communications in Statistics - Theory and Methods2023-02-21T10:59:17ZLuyuan ChenYong Denga Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, Chinab School of Medicine, Vanderbilt University, Nashville, Tennessee, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2173975https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2173975?af=RStochastic decomposition in a queueing-inventory system with batch demands, randomized order policy and multiple vacations
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. <br/>. <br/>Stochastic decomposition in a queueing-inventory system with batch demands, randomized order policy and multiple vacationsdoi:10.1080/03610926.2023.2179886Communications in Statistics - Theory and Methods2023-02-25T06:56:13ZLinhong LiLiwei LiuWei XuZhen Wanga School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, Jiangsu, Chinab School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, ChinaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2179886https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179886?af=ROn general weighted extropy of ranked set sampling
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179888?af=R
. <br/>. <br/>On general weighted extropy of ranked set samplingdoi:10.1080/03610926.2023.2179888Communications in Statistics - Theory and Methods2023-02-25T07:01:59ZNitin GuptaSantosh Kumar ChaudharyDepartment of Mathematics, Indian Institute of Technology Kharagpur, West Bengal, IndiaCommunications in Statistics - Theory and Methods11410.1080/03610926.2023.2179888https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179888?af=RAsymptotic properties of conditional U-statistics using delta sequences
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. <br/>. <br/>Asymptotic properties of conditional U-statistics using delta sequencesdoi:10.1080/03610926.2023.2179887Communications in Statistics - Theory and Methods2023-03-01T05:48:21ZSalim BouzebdaAmel Nezzala LMAC (Laboratory of Applied Mathematics of Compiègne), Université de technologie de Compiègne, Compiègne CedexCommunications in Statistics - Theory and Methods15610.1080/03610926.2023.2179887https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2179887?af=RGroup sequential hypothesis tests with variable group sizes: Optimal design and performance evaluation
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. <br/>. <br/>Group sequential hypothesis tests with variable group sizes: Optimal design and performance evaluationdoi:10.1080/03610926.2023.2231155Communications in Statistics - Theory and Methods2023-07-19T08:17:39ZAndrey NovikovMetropolitan Autonomous University, Mexico City, MexicoCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2231155https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2231155?af=ROn robustness of model selection criteria based on divergence measures: Generalizations of BHHJ divergence-based method and comparison
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. <br/>. <br/>On robustness of model selection criteria based on divergence measures: Generalizations of BHHJ divergence-based method and comparisondoi:10.1080/03610926.2022.2155788Communications in Statistics - Theory and Methods2022-12-15T01:30:37ZSumito KurataGraduate School of Information Science and Technology, The University of Tokyo, Tokyo, JapanCommunications in Statistics - Theory and Methods11810.1080/03610926.2022.2155788https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155788?af=RFlexible CDF-quantile distributions on the closed unit interval, with software and applications
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. <br/>. <br/>Flexible CDF-quantile distributions on the closed unit interval, with software and applicationsdoi:10.1080/03610926.2023.2166352Communications in Statistics - Theory and Methods2023-01-17T10:05:02ZMichael SmithsonYiyun Shoua Research School of Psychology, Australian National University, Canberra, ACT, Australiab Lloyd’s Register Foundation Institute for the Public Understanding of Risk, National University of Singapore, Singaporec Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, SingaporeCommunications in Statistics - Theory and Methods12310.1080/03610926.2023.2166352https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2166352?af=RA nonparametric test for the two-sample problem based on order statistics
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. <br/>. <br/>A nonparametric test for the two-sample problem based on order statisticsdoi:10.1080/03610926.2022.2161310Communications in Statistics - Theory and Methods2023-02-03T08:24:35ZFazil AlievLevent ÖzbekMehmet Fedai KayaCoşkun KuşHon Keung Tony NgHaikady N. Nagarajaa Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USAb Department of Statistics, Ankara University, Ankara, Turkeyc Department of Actuarial Science, Selcuk University, Konya, Turkeyd Department of Statistics, Selcuk University, Konya, Turkeye Department of Mathematical Sciences, Bentley University, Waltham, Massachusetts, USAf College of Public Health, The Ohio State University, Columbus, Ohio, USACommunications in Statistics - Theory and Methods12510.1080/03610926.2022.2161310https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2161310?af=RVariable selection for high-dimensional incomplete data using horseshoe estimation with data augmentation
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. <br/>. <br/>Variable selection for high-dimensional incomplete data using horseshoe estimation with data augmentationdoi:10.1080/03610926.2023.2177107Communications in Statistics - Theory and Methods2023-02-23T08:57:12ZYunxi ZhangSoeun Kima Department of Data Science, University of Mississippi Medical Center, Jackson, USAb Department of Mathematics, Physics, Statistics, Azusa Pacific University, Azusa, USACommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2177107https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2177107?af=RANVILS-VOCE: ANova-based Varying Inner-Loop Size estimation of Variance of Conditional Expectation
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. <br/>. <br/>ANVILS-VOCE: ANova-based Varying Inner-Loop Size estimation of Variance of Conditional Expectationdoi:10.1080/03610926.2023.2182158Communications in Statistics - Theory and Methods2023-03-01T05:56:23ZMohammed Shahid AbdullaL. Ramprasatha Information Systems Area, Indian Institute of Management, Kozhikode, Kerala, Indiab Finance, Accounting and Control Area, Indian Institute of Management, Kozhikode, Kerala, IndiaCommunications in Statistics - Theory and Methods1810.1080/03610926.2023.2182158https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2182158?af=RAnalyzing unreplicated two-level factorial designs by combining multiple tests
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. <br/>. <br/>Analyzing unreplicated two-level factorial designs by combining multiple testsdoi:10.1080/03610926.2023.2185752Communications in Statistics - Theory and Methods2023-03-08T12:33:45ZMahmood Kharrati-KopaeiZahra Shenavaria Department of Statistics, Shiraz University, Shiraz, Iranb Department of Mathematics, Faculty of Sciences, Shiraz Branch, Islamic Azad University, Shiraz, IranCommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2185752https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185752?af=RA hybrid method for density power divergence minimization with application to robust univariate location and scale estimation
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. <br/>. <br/>A hybrid method for density power divergence minimization with application to robust univariate location and scale estimationdoi:10.1080/03610926.2023.2209347Communications in Statistics - Theory and Methods2023-05-12T05:53:34ZAndrews T. AnumMichael PokojovyDepartment of Mathematical Sciences, The University of Texas at El Paso, El Paso, Texas, USACommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2209347https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2209347?af=RImproved chi-square control charts with weak-run rules
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. <br/>. <br/>Improved chi-square control charts with weak-run rulesdoi:10.1080/03610926.2023.2215357Communications in Statistics - Theory and Methods2023-05-26T11:13:11ZSpiros D. DafnisTheodoros PerdikisGeorgios K. Papadopoulosa Department of Crop Science, Agricultural University of Athens, Athens, Greeceb Department of Statistics, Athens University of Economics and Business, Athens, GreeceCommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2215357https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2215357?af=RConstruction of bivariate symmetric and asymmetric copulas and its relationship to ratios of conditional hazard rate functions
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. <br/>. <br/>Construction of bivariate symmetric and asymmetric copulas and its relationship to ratios of conditional hazard rate functionsdoi:10.1080/03610926.2023.2218505Communications in Statistics - Theory and Methods2023-06-07T08:17:21ZJan W. H. SwanepoelUnit for Data Science and Computing, North-West University, Potchefstroom, South AfricaCommunications in Statistics - Theory and Methods12110.1080/03610926.2023.2218505https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2218505?af=RPerformance evaluation of novel logarithmic estimators under correlated measurement errors
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. <br/>. <br/>Performance evaluation of novel logarithmic estimators under correlated measurement errorsdoi:10.1080/03610926.2023.2219793Communications in Statistics - Theory and Methods2023-06-07T08:20:10ZShashi BhushanAnoop KumarShivam Shuklaa Department of Statistics, University of Lucknow, Lucknow, UP, Indiab Department of Statistics, Amity University, Lucknow, UP, Indiac Department of Mathematics & Statistics, Dr. Shakuntala Misra National Rehabilitation University, Lucknow, UP, IndiaCommunications in Statistics - Theory and Methods11210.1080/03610926.2023.2219793https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2219793?af=RA new approach for semi-parametric regression analysis of bivariate interval-censored outcomes from case-cohort studies
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. <br/>. <br/>A new approach for semi-parametric regression analysis of bivariate interval-censored outcomes from case-cohort studiesdoi:10.1080/03610926.2023.2220850Communications in Statistics - Theory and Methods2023-06-10T02:51:56ZYichen LouPeijie WangJianguo Suna School of Mathematics, Jilin University, Changchun, Chinab Department of Statistics, University of Missouri, Columbia, Missouri, USACommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2220850https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220850?af=RTwo-sample test based on maximum variance discrepancy
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. <br/>. <br/>Two-sample test based on maximum variance discrepancydoi:10.1080/03610926.2023.2220851Communications in Statistics - Theory and Methods2023-06-13T08:41:01ZN. MakigusaGraduate School of Nanobioscience, Yokohama City University, Yokohama, JapanCommunications in Statistics - Theory and Methods11810.1080/03610926.2023.2220851https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220851?af=RConfidence intervals in general regression models that utilize uncertain prior information
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2243528?af=R
. <br/>. <br/>Confidence intervals in general regression models that utilize uncertain prior informationdoi:10.1080/03610926.2023.2243528Communications in Statistics - Theory and Methods2023-08-11T06:51:52ZPaul KabailaNishika RanathungaDepartment of Mathematical and Physical Sciences, La Trobe University, Bundoora, Victoria, AustraliaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2243528https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2243528?af=REstimation of a clustering model for non Gaussian functional data
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246089?af=R
. <br/>. <br/>Estimation of a clustering model for non Gaussian functional datadoi:10.1080/03610926.2023.2246089Communications in Statistics - Theory and Methods2023-08-18T02:18:13ZXu TengtengXiuzhen ZhangRiquan Zhanga School of Science, Nantong University, Nantong, China.b School of Mathematics and Statistics, Shanxi Datong University, Datong China.c School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China.Communications in Statistics - Theory and Methods11510.1080/03610926.2023.2246089https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2246089?af=RSmoothed empirical likelihood for optimal cut point analysis
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244096?af=R
. <br/>. <br/>Smoothed empirical likelihood for optimal cut point analysisdoi:10.1080/03610926.2023.2244096Communications in Statistics - Theory and Methods2023-08-21T11:32:00ZRong LiuChunjie WangYujing YaoZhezhen Jina School of Mathematics and Statistics, Changchun University of Technology, Changchun, P.R. China.b Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York, USACommunications in Statistics - Theory and Methods11610.1080/03610926.2023.2244096https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2244096?af=RTesting symmetry of model errors for non linear multiplicative distortion measurement error models
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2245639?af=R
. <br/>. <br/>Testing symmetry of model errors for non linear multiplicative distortion measurement error modelsdoi:10.1080/03610926.2023.2245639Communications in Statistics - Theory and Methods2023-08-24T06:11:52ZJun ZhangZhenghui FengYue Zhoua College of Mathematics and Statistics, Shenzhen University, Shenzhen, Guangdong, China.b School of Science, Harbin Institute of Technology, Shenzhen, Guangdong, China.Communications in Statistics - Theory and Methods12210.1080/03610926.2023.2245639https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2245639?af=REfficient non parametric spectral density estimation with censored observations
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250484?af=R
. <br/>. <br/>Efficient non parametric spectral density estimation with censored observationsdoi:10.1080/03610926.2023.2250484Communications in Statistics - Theory and Methods2023-08-26T06:24:23ZSam EfromovichJiaju WuDepartment of Mathematical Sciences, The University of Texas at Dallas, Richardson, Texas, USACommunications in Statistics - Theory and Methods12410.1080/03610926.2023.2250484https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2250484?af=RJackknife model averaging for additive expectile prediction
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2251625?af=R
. <br/>. <br/>Jackknife model averaging for additive expectile predictiondoi:10.1080/03610926.2023.2251625Communications in Statistics - Theory and Methods2023-09-04T03:06:03ZXianwen SunLixin ZhangSchool of Mathematical Sciences, Zhejiang University, Hangzhou, People’s Republic of ChinaCommunications in Statistics - Theory and Methods13310.1080/03610926.2023.2251625https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2251625?af=RBayesian analysis for two-part latent variable model with application to fractional data
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. <br/>. <br/>Bayesian analysis for two-part latent variable model with application to fractional datadoi:10.1080/03610926.2023.2273205Communications in Statistics - Theory and Methods2023-10-27T05:57:31ZJinye ChenLinyi ZhengYemao Xiaa College of Economics and Management, Nanjing Forestry University, Nanjing, Jiangsu, Chinab Department of Applied Mathematics, Nanjing Forestry University, Nanjing, Jiangsu, ChinaCommunications in Statistics - Theory and Methods12910.1080/03610926.2023.2273205https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2273205?af=RTesting ANOVA effects: A resolution for unbalanced models
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2274808?af=R
. <br/>. <br/>Testing ANOVA effects: A resolution for unbalanced modelsdoi:10.1080/03610926.2023.2274808Communications in Statistics - Theory and Methods2023-11-03T06:12:49ZLynn R. LaMotteBiostatistics Program, School of Public Health, LSU Health New Orleans, New Orleans, Louisiana, USACommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2274808https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2274808?af=RNon parametric regression models with additive distortions
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281894?af=R
. <br/>. <br/>Non parametric regression models with additive distortionsdoi:10.1080/03610926.2023.2281894Communications in Statistics - Theory and Methods2023-11-22T06:18:11ZYujie GaiJun ZhangYiping Yanga School of Statistics and Mathematics, Central University of Finance and Economics, Beijing, Chinab School of Mathematical Sciences, Shenzhen University, Shenzhen, Chinac College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, ChinaCommunications in Statistics - Theory and Methods12210.1080/03610926.2023.2281894https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281894?af=RRefinements on the exact method to solve the numerical difficulties in fitting the log binomial regression model for estimating relative risk
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2284674?af=R
. <br/>. <br/>Refinements on the exact method to solve the numerical difficulties in fitting the log binomial regression model for estimating relative riskdoi:10.1080/03610926.2023.2284674Communications in Statistics - Theory and Methods2023-11-24T11:37:51ZChao ZhuDavid W. HosmerJim StankovichKaren WillsLeigh Blizzarda Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australiab Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australiac Department of Mathematics and Statistics, University of Vermont, Burlington, Vermont, USACommunications in Statistics - Theory and Methods11710.1080/03610926.2023.2284674https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2284674?af=RExpected spacing
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281265?af=R
. <br/>. <br/>Expected spacingdoi:10.1080/03610926.2023.2281265Communications in Statistics - Theory and Methods2023-12-09T11:07:21ZGreg KreiderPrimordial Machine Vision Systems, Lyndeborough, New Hampshire, USACommunications in Statistics - Theory and Methods11110.1080/03610926.2023.2281265https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2281265?af=REstimation of correlation coefficient with monotone transformation and multiplicative distortions
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2288794?af=R
. <br/>. <br/>Estimation of correlation coefficient with monotone transformation and multiplicative distortionsdoi:10.1080/03610926.2023.2288794Communications in Statistics - Theory and Methods2023-12-09T11:30:31ZJun ZhangXuan YuSiming DengJiongTao ZhongYisheng ZhouBingqing LinSchool of Mathematical Sciences, Shenzhen University, Shenzhen, Guangdong, China.Communications in Statistics - Theory and Methods13310.1080/03610926.2023.2288794https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2288794?af=RCovariance ratio under multiplicative distortion measurement errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2295240?af=R
. <br/>. <br/>Covariance ratio under multiplicative distortion measurement errorsdoi:10.1080/03610926.2023.2295240Communications in Statistics - Theory and Methods2023-12-25T09:49:41ZJiongtao ZhongSiming DengJun ZhangZhenghui Fenga School of Mathematical Sciences, Shenzhen University, Shenzhen, Chinab School of Science, Harbin Institute of Technology, Shenzhen, Guangdong, ChinaCommunications in Statistics - Theory and Methods13310.1080/03610926.2023.2295240https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2295240?af=RBayesian mediation analysis for time-to-event outcome: Investigating racial disparity in breast cancer survival
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. <br/>. <br/>Bayesian mediation analysis for time-to-event outcome: Investigating racial disparity in breast cancer survivaldoi:10.1080/03610926.2024.2307461Communications in Statistics - Theory and Methods2024-02-08T11:59:40ZQingzhao YuWentao CaoDonald MercanteBiostatistics, School of Public Health, LSU Health-New Orleans, New Orleans, Louisiana, USACommunications in Statistics - Theory and Methods11710.1080/03610926.2024.2307461https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2307461?af=RA simple INAR(1) model for analyzing count time series with multiple features
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2314613?af=R
. <br/>. <br/>A simple INAR(1) model for analyzing count time series with multiple featuresdoi:10.1080/03610926.2024.2314613Communications in Statistics - Theory and Methods2024-02-21T11:03:18ZYao KangDanshu ShengFeilong Lua School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Chinab School of Mathematics and Statistics, Liaoning University, Shenyang, Chinac School of Science, University of Science and Technology Liaoning, Anshan, ChinaCommunications in Statistics - Theory and Methods11910.1080/03610926.2024.2314613https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2314613?af=RMultistate models with nested frailty for lifetime analysis: Application to bone marrow transplantation recovery patients
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2313042?af=R
. <br/>. <br/>Multistate models with nested frailty for lifetime analysis: Application to bone marrow transplantation recovery patientsdoi:10.1080/03610926.2024.2313042Communications in Statistics - Theory and Methods2024-02-21T11:16:41ZJonathan K. J. VasquezKaty C. MolinaVera TomazellaCarlos A. DinizAdriano K. Suzukia Institute of Mathematics and Computer Sciences, University of S∼ao Paulo, S∼ao Carlos, S∼ao Paulo, Brazilb Department of Statistics, Federal University of S∼ao Carlos, S∼ao Carlos, S∼ao Paulo, BrazilCommunications in Statistics - Theory and Methods11910.1080/03610926.2024.2313042https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2313042?af=RCalibration estimator for a sensitive variable using dual auxiliary information under measurement errors
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2322617?af=R
. <br/>. <br/>Calibration estimator for a sensitive variable using dual auxiliary information under measurement errorsdoi:10.1080/03610926.2024.2322617Communications in Statistics - Theory and Methods2024-03-07T10:43:10ZZhiqiang PangXijuan NiuZhaoxu WangJingchen Youa School of Statistics, Lanzhou University of Finance and Economics, Lanzhou, Gansu, Chinab School of Mathematics and Statistics, Qinghai Normal University, Xining, Qinghai, Chinac School of Statistics, Xi’an University of Finance and Economics, Xi’an, Shaanxi, ChinaCommunications in Statistics - Theory and Methods11810.1080/03610926.2024.2322617https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2322617?af=REquivalence of state equations from different methods in high-dimensional regression
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2322616?af=R
. <br/>. <br/>Equivalence of state equations from different methods in high-dimensional regressiondoi:10.1080/03610926.2024.2322616Communications in Statistics - Theory and Methods2024-03-18T12:26:27ZSaidi LuoSongtao Tiana Center for Statistical Science, Tsinghua University, Beijing, Chinab Department of Mathematical Sciences, Tsinghua University, Beijing, ChinaCommunications in Statistics - Theory and Methods11410.1080/03610926.2024.2322616https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2322616?af=RMinimum density power divergence estimation for the generalized exponential distribution
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329768?af=R
. <br/>. <br/>Minimum density power divergence estimation for the generalized exponential distributiondoi:10.1080/03610926.2024.2329768Communications in Statistics - Theory and Methods2024-03-22T06:20:44ZArnab HazraDepartment of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, India.Communications in Statistics - Theory and Methods12110.1080/03610926.2024.2329768https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329768?af=RComplete convergence theorems for moving average process generated by independent random variables under sub-linear expectations
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220449?af=R
. <br/>. <br/>Complete convergence theorems for moving average process generated by independent random variables under sub-linear expectationsdoi:10.1080/03610926.2023.2220449Communications in Statistics - Theory and Methods2023-06-08T06:40:27ZXiaocong ChenQunying WuCollege of Science, Guilin University of Technology, Guilin, PR ChinaCommunications in Statistics - Theory and Methods12710.1080/03610926.2023.2220449https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2220449?af=RRun orders in factorial designs: A literature review
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185472?af=R
. <br/>. <br/>Run orders in factorial designs: A literature reviewdoi:10.1080/03610926.2023.2185472Communications in Statistics - Theory and Methods2023-03-09T11:00:17ZRomario A. Conto LópezAlexander A. Correa EspinalOlga C. Úsuga Mancoa Instituto Tecnológico Metropolitano (ITM), Medellín, Colombiab Departamento de Ingeniería de la Organización, Universidad Nacional de Colombia, Medellín, Colombiac Departamento de Ingeniería Industrial, Universidad de Antioquia, Medellín, ColombiaCommunications in Statistics - Theory and Methods11910.1080/03610926.2023.2185472https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2185472?af=RZero-inflated Poisson INAR(1) model with periodic structure
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329241?af=R
. <br/>. <br/>Zero-inflated Poisson INAR(1) model with periodic structuredoi:10.1080/03610926.2024.2329241Communications in Statistics - Theory and Methods2024-03-21T10:27:43ZAbderrahmen ManaaRoufaida Souakria Higher National School of Biotechnology Taoufik Khaznadar, nouveau pôle universitaire Ali Mendili, BP. E66, Constantine, 25100, Algeriab Faculty of Mathematics, University of Science and Technology Houari Boumediene, Algiers, AlgeriaCommunications in Statistics - Theory and Methods12110.1080/03610926.2024.2329241https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2329241?af=RDistribution of big claims in a Lévy insurance risk process: Analytics of a new non-parametric estimator
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2323634?af=R
. <br/>. <br/>Distribution of big claims in a Lévy insurance risk process: Analytics of a new non-parametric estimatordoi:10.1080/03610926.2024.2323634Communications in Statistics - Theory and Methods2024-03-25T11:53:58ZSharif MozumderM. Kabir HassanGhulam SorwarJosé Antonio Pérez Amuedoa Department of Mathematics, University of Dhaka, Dhaka, Bangladeshb Finance and Economics, University of New Orleans, New Orleans, Louisiana, USAc Keele Business School, Keele University, Keele, UKSharif Mozumder holds PhD in Mathematical Finance from Nottingham University, UK, and current Professor of Mathematics at University of Dhaka, Bangladesh. He has published articles in Review of Quantitative Finance and Accounting, Journal of Financial Engineering, Applied Economics, Annals of Financial Economics, Economic Modeling, Global Finance Journal, Computational Economics, among others.M. Kabir Hassan is a Distinguished Professor of Finance at the University of New Orleans, USA. He has published 472+ articles in the Journal of Corporate Finance, Journal of Banking and Finance, Journal of International Money and Finance, Review of Quantitative Finance and Accounting, Pacific Basic Finance Journal, Economic Modeling, Quarterly Review of Economics and Finance, Journal of Financial Stability, Journal of Business Finance and Accounting, among others. He has won 39 Best Paper Awards from Academic Conference presentations. His Google Scholar H-index is 86. He has presented over 520 research articles at professional conferences and has delivered 360 invited articles/seminars. Professor Hassan is the Editor-in-Chief of the International Journal of Islamic and Middle Eastern Finance and Management, Editor of the Quarterly Journal of Finance and Accounting, and Editor of the Journal of Economic Cooperation and Development. He is Associate Editor of the Global Finance Journal, Review of International Business and Finance, International Review of Economics and Finance, and Pacific-Basin Finance Journal. Professor Hassan has won the 2016 Islamic Development Bank Prize for his contribution to scholarly research in Islamic banking and finance.Ghulam Sorwar holds PhD from City University Business School now known as Cass Business School. He is a professor in finance at Keele University, UK.José Antonio Pérez Amuedo is a Ph.D. candidate at the University of New Orleans, USA.Communications in Statistics - Theory and Methods12610.1080/03610926.2024.2323634https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2323634?af=RLetter to the editor: on the paper “The double Pareto-Lognormal distribution—a new parametric model for size distributions” and its correction
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2174788?af=R
. <br/>. <br/>Letter to the editor: on the paper “The double Pareto-Lognormal distribution—a new parametric model for size distributions” and its correctiondoi:10.1080/03610926.2023.2174788Communications in Statistics - Theory and Methods2023-02-21T11:06:33ZNeven GrbacTihana Galinac GrbacJuraj Dobrila University of Pula, Pula, CroatiaCommunications in Statistics - Theory and Methods1310.1080/03610926.2023.2174788https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2174788?af=RErrata: Interval estimation, point estimation, and null hypothesis significance testing calibrated by an estimated posterior probability of the null hypothesis Bickel (2023)
https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2203788?af=R
. <br/>. <br/>Errata: Interval estimation, point estimation, and null hypothesis significance testing calibrated by an estimated posterior probability of the null hypothesis Bickel (2023)doi:10.1080/03610926.2023.2203788Communications in Statistics - Theory and Methods2023-04-22T04:56:48ZDavid R. BickelInformatics and Analytics, University of North Carolina at Greensboro, The Graduate School, Greensboro, North Carolina, USACommunications in Statistics - Theory and Methods1110.1080/03610926.2023.2203788https://www.tandfonline.com/doi/full/10.1080/03610926.2023.2203788?af=RKernel-based method for joint independence of functional variables
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2326545?af=R
. <br/>. <br/>Kernel-based method for joint independence of functional variablesdoi:10.1080/03610926.2024.2326545Communications in Statistics - Theory and Methods2024-03-13T05:19:36ZTerence Kevin Manfoumbi DjonguetGuy Martial NkietUniversité des Sciences et Techniques de Masuku, Franceville, GabonCommunications in Statistics - Theory and Methods11710.1080/03610926.2024.2326545https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2326545?af=R