Skip to content

Monte Carlo Methods in Bayesian Computation

Best in textbook rentals since 2012!

ISBN-10: 0387989358

ISBN-13: 9780387989358

Edition: 2000

Authors: Ming-Hui Chen, Qi-Man Shao, Joseph G. Ibrahim, Peter J. Bickel, P. Diggle

List price: $109.99
Shipping box This item qualifies for FREE shipping.
Blue ribbon 30 day, 100% satisfaction guarantee!
Rent eBooks
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!

Description:

This book examines advanced Bayesian computational methods. It presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo methods for estimation of posterior quantities, improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations,…    
Customers also bought

Book details

List price: $109.99
Copyright year: 2000
Publisher: Springer New York
Publication date: 1/21/2000
Binding: Hardcover
Pages: 387
Size: 6.10" wide x 9.25" long x 0.38" tall
Weight: 3.630
Language: English

Louis Chen�s research interests are in probability and computational biology, focusing largely on Stein�s method. He is well-known for his pioneering work on Poisson approximation. He is an elected Fellow of the Institute of Mathematical Statistics and of the Academy of Sciences for the Developing World. He has also served as Associate Editor of Statistica Sinica and Bernoulli.Larry Goldstein has studied Stein�s method since 1989, and is a noted researcher in the field. He was elected Fellow of the Institute of Mathematical Statistics in 2003, and serves on the editorial board of Bernoulli.Qi-Man Shao has been working on limit theory in probability and statistics, especially on…    

Introduction
Markov Chain Monte Carlo Sampling
Basic Monte Carlo Methods for Estimating Posterior Quantities
Estimating Marginal Posterior Densities
Estimating Ratios of Normalizing Constants
Monte Carlo Methods for Constrained Parameter Problems
Computing Bayesian Credible and HPD Intervals
Bayesian Approaches for Comparing Non-Nested Models
Bayesian Variable Section
Other Topics