[PDF.32zf] Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)

Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)

[PDF.pr12] Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)

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 | #267186 in Books |  2001-10-05 | Original language:English | PDF # 1 |  9.21 x.94 x6.14l,1.58 | File type: PDF | 387 pages

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||27 of 28 people found the following review helpful.| MCMC methods presente for efficient and realistic application of Bayesian methods|By Michael R. Chernick|With advances in computing and the rediscovery of Markov Chain Monte Carlo methods and their application to Bayesian methods, there have been a number of books written on this subject in recent years. What then distinguishes this text from the others?

Section 1.| |"This book combines the theory topics with good computer and application examples from the field of food science, agriculture, cancer and others. The volume will provide an excellent research resource for statisticians with an interest in computer intensive me

Dealing with methods for sampling from posterior distributions and how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples, this book addresses such topics as improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models...

You can specify the type of files you want, for your gadget.Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)   |  Ming-Hui Chen, Qi-Man Shao, Joseph G. Ibrahim. A good, fresh read, highly recommended.

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