Abstract #300611

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JSM 2002 Abstract #300611
Activity Number: 303
Type: Topic Contributed
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing*
Abstract - #300611
Title: Honest Exploration of Intractable Probability Distributions Via Markov Chain Monte Carlo
Author(s): James Hobert*+ and Galin Jones
Affiliation(s): University of Florida and University of Minnesota
Address: 203 Griffin-Floyd Hall, Gainesville, Florida, 32611, USA
Keywords: Minorization condition ; Central limit theorem ; Convergence rate ; Drift condition ; Regeneration
Abstract:

Two important questions that must be answered whenever a Markov chain Monte Carlo algorithm is used are (Q1) What is an appropriate burn-in? and (Q2) How long should the sampling continue after burn-in? One method of developing rigorous answers to these questions involves establishing drift and minorization conditions, which together imply that the underlying Markov chain is geometrically ergodic. In this talk, I will explain exactly what drift and minorization are, as well as how and why these conditions can be used to form rigorous answers to (Q1) and (Q2).

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Revised March 2002