Handbook of Markov Chain Monte Carlo PDF
Edited by Steve (University of Cambridge, Cambridge, England, UK) Brooks, Andrew (Columbia University, New York, New York, USA) Gelman, Galin (University of Minnesota, Minneapolis, Minnesota, USA) Jones, Xiao-Li (Harvard university) Meng
Part of the Chapman & Hall/CRC Handbooks of Modern Statistical Methods series
Description
Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics.
Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisherie
Information
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Download - Immediately Available
- Format:PDF
- Pages:619 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:10/05/2011
- Category:
- ISBN:9781420079425
Information
-
Download - Immediately Available
- Format:PDF
- Pages:619 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:10/05/2011
- Category:
- ISBN:9781420079425