Bayesian Computation with R by Jim Albert.

There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for stat...

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Bibliographic Details
Main Author:	Albert, Jim (Author)
Corporate Author:	SpringerLink (Online service)
Format:	eBook
Language:	English
Published:	New York, NY : Springer New York : Imprint: Springer, 2007.
Edition:	1st ed. 2007.
Series:	Use R!, Springer eBook Collection.
Subjects:	Statistics . Computer simulation. Computer mathematics. Mathematics. Visualization. Mathematical optimization. Electronic resources (E-books)
Online Access:	Click to view e-book
Holy Cross Note:	Loaded electronically. Electronic access restricted to members of the Holy Cross Community.

Table of Contents:

An Introduction to R
to Bayesian Thinking
Single-Parameter Models
Multiparameter Models
to Bayesian Computation
Markov Chain Monte Carlo Methods
Hierarchical Modeling
Model Comparison
Regression Models
Gibbs Sampling
Using R to Interface with WinBUGS.

Bayesian Computation with R by Jim Albert.

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