Open Access
December 2017 Fast Simulation of Hyperplane-Truncated Multivariate Normal Distributions
Yulai Cong, Bo Chen, Mingyuan Zhou
Bayesian Anal. 12(4): 1017-1037 (December 2017). DOI: 10.1214/17-BA1052

Abstract

We introduce a fast and easy-to-implement simulation algorithm for a multivariate normal distribution truncated on the intersection of a set of hyperplanes, and further generalize it to efficiently simulate random variables from a multivariate normal distribution whose covariance (precision) matrix can be decomposed as a positive-definite matrix minus (plus) a low-rank symmetric matrix. Example results illustrate the correctness and efficiency of the proposed simulation algorithms.

Citation

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Yulai Cong. Bo Chen. Mingyuan Zhou. "Fast Simulation of Hyperplane-Truncated Multivariate Normal Distributions." Bayesian Anal. 12 (4) 1017 - 1037, December 2017. https://doi.org/10.1214/17-BA1052

Information

Published: December 2017
First available in Project Euclid: 1 March 2017

zbMATH: 1384.65014
MathSciNet: MR3724977
Digital Object Identifier: 10.1214/17-BA1052

Keywords: Cholesky decomposition , conditional distribution , equality constraints , high-dimensional regression , structured covariance/precision matrix

Vol.12 • No. 4 • December 2017
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