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Original Articles

A Simple New Algorithm for Quadratic Programming with Applications in Statistics

Pages 1126-1139
Received 03 Dec 2009
Accepted 10 Jan 2012
Published online: 12 Dec 2012
 
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Problems involving estimation and inference under linear inequality constraints arise often in statistical modeling. In this article, we propose an algorithm to solve the quadratic programming problem of minimizing for positive definite Q, where is constrained to be in a closed polyhedral convex cone , and the m × n matrix is not necessarily full row rank. The three-step algorithm is intuitive and easy to code. Code is provided in the R programming language.

Acknowledgment

This work was partially supported by NSF DMS 0905656.