Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference
商品資訊
系列名:Texts in Statistical Science Series
ISBN13:9781584885870
出版社:Chapman & Hall
作者:Dani Gamerman; Hedibert Freitas Lopes
出版日:2006/05/17
裝訂/頁數:精裝/323頁
規格:23.5cm*15.9cm*1.9cm (高/寬/厚)
商品簡介
Major changes from the previous edition:
· More examples with discussion of computational details in chapters on Gibbs sampling and Metropolis-Hastings algorithms
· Recent developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection
· Discussion of computation using both R and WinBUGS
· Additional exercises and selected solutions within the text, with all data sets and software available for download from the Web
· Sections on spatial models and model adequacy
The self-contained text units make MCMC accessible to scientists in other disciplines as well as statisticians. The book will appeal to everyone working with MCMC techniques, especially research and graduate statisticians and biostatisticians, and scientists handling data and formulating models. The book has been substantially reinforced as a first reading of material on MCMC and, consequently, as a textbook for modern Bayesian computation and Bayesian inference courses.
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