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Activity Number: 524
Type: Topic Contributed
Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #316250
Title: A Modified Conditional Metropolis-Hastings Sampler
Author(s): Alicia Johnson*
Companies: Macalester College
Keywords: Markov chain Monte Carlo ; geometric ergodicity ; Metropolis-Hastings sampler ; Gibbs sampler
Abstract:

A modified conditional Metropolis-Hastings sampler for general state spaces is introduced. Under specified conditions, this modification can lead to substantial gains in statistical efficiency while maintaining the overall quality of convergence. Results are illustrated in two settings: a toy bivariate Normal model and a Bayesian version of the random effects model.


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