A Modified Gibbs Sampler on General State Spaces

2013/08/26 by Alicia A. Johnson, James M. Flegal, Johnson, Alicia A. +1
Computer Science · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference #stat.CO

paper · pdf · doi:10.48550/arxiv.1308.5717

arxiv created 2013/08/26 · openalex publication_date 2013/08/26 · arxiv updated 2013/08/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We present a modified Gibbs sampler for general state spaces. We establish that this modification can lead to substantial gains in statistical efficiency while maintaining the overall quality of convergence. We illustrate our results in two examples including a toy Normal-Normal model and a Bayesian version of the random effects model.

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