A note on simulating hyperplane-truncated multivariate normal distributions

Hassan Maatouk, Xavier Bay and Didier Rullière

Statistics & Probability Letters, 2022, vol. 191, issue C

Abstract: Statistical researchers have shown increasing interest in generating conditional multivariate normal distributions. In this paper, we discuss several existing methods for the simulation of multivariate normal distribution truncated on the intersection of a set of hyperplanes. We also propose an approach based on the consideration of an orthonormal basis on the set of constraints. Contrarily to the standard approaches, we do not need to compute the covariance matrix of the posterior distribution and its decomposition. The interest of the proposed approach is shown through numerical examples.

Keywords: Conditional Gaussian vectors; Hyperplanes; Projection; Orthonormal basis (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715222001730
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:191:y:2022:i:c:s0167715222001730

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spl.2022.109650

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().