On the geometrical convergence of Gibbs sampler in Rd

JOURNAL OF MULTIVARIATE ANALYSIS

卷:66

Article

Hwang, CR ; Sheu, SJ

关键词: stochastic relaxation;    Gibbs sampler;    Markov chain;    geometrical convergence;    Harris recurrence;    Monte Carlo Markov chain;    Metropolis algorithm;    nonlinear autoregression;   

DOI  :  10.1006/jmva.1997.1735

来源: Elsevier

【 摘 要 】

The geometrical convergence of the Gibbs sampler for simulating a probability distribution in R-d is proved. The distribution has a density which is a bounded perturbation of a log-concave function and satisfies some growth conditions. The analysis is based on a representation of the Gibbs sampler and some powerful results from the theory of Harris recurrent Markov chains. (C) 1998 Academic Press.

【 授权许可】

Free