论文信息 - Subsampling the Gibbs Sampler

Subsampling the Gibbs Sampler

Abstract This article provides a justification of the ban against sub-sampling the output of a stationary Markov chain that is suitable for presentation in undergraduate and beginning graduate-level courses. The justification does not rely on reversibility of the chain as does Geyer's (1992) argument and so applies to the usual implementation of the Gibbs sampler.

L. Mark Berliner | Steven N. MacEachern | S. MacEachern | L. Berliner

[1] Alan E. Gelfand,et al. Bayesian statistics without tears: A sampling-resampling perspective , 1992 .

[2] William Feller,et al. An Introduction to Probability Theory and Its Applications , 1951 .

[3] P. A. P. Moran,et al. An introduction to probability theory , 1968 .

[4] Jim Albert,et al. A Bayesian Analysis of a Poisson Random Effects Model for Home Run Hitters , 1992 .

[5] Adrian F. M. Smith,et al. Bayesian computation via the gibbs sampler and related markov chain monte carlo methods (with discus , 1993 .

[6] J. Besag,et al. Spatial Statistics and Bayesian Computation , 1993 .

[7] Gwilym M. Jenkins,et al. Time series analysis, forecasting and control , 1972 .

[8] Gwilym M. Jenkins,et al. Time series analysis, forecasting and control , 1971 .

[9] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[10] Luke Tierney. [Practical Markov Chain Monte Carlo]: Comment , 1992 .

[11] George E. P. Box,et al. Time Series Analysis: Forecasting and Control , 1977 .

[12] Charles J. Geyer,et al. Practical Markov Chain Monte Carlo , 1992 .

[13] Jim Albert. Teaching Bayesian Statistics Using Sampling Methods and MINITAB , 1993 .

[14] G. Casella,et al. Explaining the Gibbs Sampler , 1992 .