Optimal scaling of Metropolis algorithms: Heading toward general target distributions-Reference-Cited by-同舟云学术

Optimal scaling of Metropolis algorithms: Heading toward general target distributions

Published:2008-12 Issue:4 Volume:36 Page:483-503
ISSN:0319-5724
Container-title:Canadian Journal of Statistics
language:en
Short-container-title:Can. J. Statistics

Author:

BÃ©dard MylÃ¨ne,Rosenthal Jeffrey S.

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/cjs.5550360401/fullpdf

Reference25 articles.

1. M. BÃ©dard (2006). On the Robustness of Optimal Scaling for Random Walk Metropolis Algorithms. Doctoral dissertation, Department of Statistics, University of Toronto.

2. Weak convergence of Metropolis algorithms for non-iid target distributions;BÃ©dard;The Annals of Applied Probability,2007

3. M. BÃ©dard (2007b). Optimal acceptance rates for Metropolis algorithms: Moving beyond 0.234. Stochastic Processes and their Applications, In press: corrected proof available online 31 December 2007.

4. Efficient sampling using Metropolis algorithms: Applications of optimal scaling results;BÃ©dard;Journal of Computational and Graphical Statistics,2008

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