Behaviour of the Gibbs sampler when conditional distributions are potentially incompatible

DOI10.1080/00949655.2014.968159OpenAlexW2066238105WikidataQ43248312 ScholiaQ43248312MaRDI QIDQ5222282

Shyh-Huei Chen, Edward H. Ip

Publication date: 1 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4572746

zbMATH Keywords

Gibbs samplerGibbs chainpotentially incompatible conditional-specified distribution

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

A perfect sampling method for exponential family random graph models ⋮ Exactly and almost compatible joint distributions for high-dimensional discrete conditional distributions ⋮ Full conditional distributions for Bayesian multilevel models with additive or interactive effects and missing data on covariates ⋮ Likelihood-free approximate Gibbs sampling ⋮ Extending balance assessment for the generalized propensity score under multiple imputation

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimizing random scan Gibbs samplers
• Gibbs ensembles for nearly compatible and incompatible conditional models
• Non-negative matrices and Markov chains. 2nd ed
• Exact and near compatibility of discrete conditional distributions
• Epidemiology and medical statistics
• 10.1162/153244301753344614
• Sampling-Based Approaches to Calculating Marginal Densities
• Fully conditional specification in multivariate imputation
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Markov Chains
• Monte Carlo sampling methods using Markov chains and their applications
• Lectures on Monte Carlo methods

This page was built for publication: Behaviour of the Gibbs sampler when conditional distributions are potentially incompatible