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The present paper develops a procedure for simulating multivariate data with count and continuous variables with a pre-specified correlation matrix. The count and continuous variables are assumed to have Poisson and normal marginals, respectively. The data generation mechanism is a combination of the normal to anything principle and a newly established connection between Poisson and normal correlations in the mixture. A step-by-step algorithm is provided and its performance is evaluated using two simulated and one real-data scenarios.

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