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Conditional simulation from highly structured Gaussian systems, with application to blocking-MCMC for the Bayesian analysis of very large linear models

Lookup NU author(s): Professor Darren Wilkinson, Stephen Yeung

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Abstract

This paper examines strategies for simulating exactly from large Gaussian linear models conditional on some Gaussian observations. Local computation strategies based on the conditional independence structure of the model are developed in order to reduce costs associated with storage and computation. Application of these algorithms to simulation from nested hierarchical linear models is considered, and the construction of efficient MCMC schemes for Bayesian inference in high-dimensional linear models is outlined.

Publication metadata

Author(s): Wilkinson DJ; Yeung SKH

Publication type: Article

Publication status: Published

Journal: Statistics and Computing

Year: 2002

Volume: 12

Issue: 3

Pages: 287-300

ISSN (print): 0960-3174

ISSN (electronic): 1573-1375

Publisher: Springer

URL: http://dx.doi.org/10.1023/A:1020711129064

DOI: 10.1023/A:1020711129064

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