2005/05/25 by Pedro J. Fernandez, Pedro J. Fernández, Fernandez, Pedro J. +5
Computer Science · Mathematics · #60G10 #60G15 #65C05 #Bayesian Methods and Mixture Models #FOS: Mathematics #Probability (math.PR) #Statistics Theory (math.ST) #math.PR #math.ST #msc:60G10 #msc:60G15 #msc:65C05 #stat.TH
paper · pdf · doi:10.48550/arxiv.math/0505522
22 pages, submitted to Journal of Applied Probability
openalex publication_date 2005/05/25 · arxiv created 2007/09/25 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The target measure μ is the distribution of a random vector in a box \cB, a Cartesian product of bounded intervals. The Gibbs sampler is a Markov chain with invariant measure μ. A ``coupling from the past'' construction of the Gibbs sampler is used to show ergodicity of the dynamics and to perfectly simulate μ. An algorithm to sample vectors with multinormal distribution truncated to \cB is then implemented.