Description: Book DetailsTitle: Bayesian Computation with R (Use R) Item Condition:used item in a very good conditionAuthor:Jim Albert ISBN 10:0387713840Publisher:Springer ISBN 13:9780387713847Published On:2008-06-11 SKU:7719-9780387713847Binding:Paperback Language: Not SpecifiedEdition:1st ed. 2007. Corr. 2nd printing List Price:-Description 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 statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry. Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The early chapters present the basic tenets of Bayesian thinking by use of familiar one and two-parameter inferential problems. Bayesian computational methods such as Laplace's method, rejection sampling, and the SIR algorithm are illustrated in the context of a random effects model. The construction and implementation of Markov Chain Monte Carlo (MCMC) methods is introduced. These simulation-based algorithms are implemented for a variety of Bayesian applications such as normal and binary response regression, hierarchical modeling, order-restricted inference, and robust modeling. Algorithms written in R are used to develop Bayesian tests and assess Bayesian models by use of the posterior predictive distribution. The use of R to interface with WinBUGS, a popular MCMC computing language, is described with several illustrative examples. This book is a suitable companion book for an introductory course on Bayesian methods and is valuable to the statistical practitioner who wishes to learn more about the R language and Bayesian methodology. The LearnBayes package, written by the author and available from the CRAN website, contains all of the R functions described in the book. The second edition contains several new topics such as the use of mixtures of conjugate priors and the use of Zellnerâs g priors to choose between models in linear regression. There are more illustrations of the construction of informative prior distributions, such as the use of conditional means priors and multivariate normal priors in binary regressions. The new edition contains changes in the R code illustrations according to the latest edition of the LearnBayes package. At AwesomeBooks we believe that good quality and speed of service is what pleases our customers and according to this we have a product guarantee on all our books. All used books sold by AwesomeBooks:Will be clean, not soiled or stained.All pages will be present and undamaged.Books will be free of page markings.Some pages may be slightly dog-eared through previous use.The spine may show some creasing through previous use.Ultimately we would never send any book we would not pick up and read ourselves. All new books sold by AwesomeBooks:Will be completely new and unfolded.Wrapped carefully to prevent damage or curling of book edges.100% money back guarantee If you are not satisfied for any reason, simply drop us an email and we will give you a 100% refund upon returning the item. If you are not happy then neither are we. If your order has not be reached you within a maximum of 21 days please contact us and we will respond immediately to help. Return Policy At AwesomeBooks, we believe our customers should feel free to order any of our products in the knowledge that they can return anything back within 30 days of purchasing an item for any reason. We will not make it awkward, if you want to return something then all you have to do is ask! Simply drop us an email to the address given on your order confirmation email or login to your paypal account used for payment and send us an email from there. For defects or problems caused before receipt of an item we will of course provide full instructions on how to return the item to us. For other issues (perhaps you did not like a product or it did not live up to expectations), we are happy to refund all costs but require the buyer to pay the return postage cost. Once you drop us an email requesting a return, we will let you know the precise return method quickly and conveniently.
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Title: Bayesian Computation with R (Use R)
Number of Pages: 267 Pages
Publication Name: Bayesian Computation with R
Language: English
Publisher: Springer
Publication Year: 2007
Item Height: 0.6 in
Subject: Programming Languages / General, Number Systems, Probability & Statistics / General, Computer Simulation, Probability & Statistics / Bayesian Analysis
Item Weight: 13.9 Oz
Type: Textbook
Author: Jim Albert
Subject Area: Mathematics, Computers
Item Length: 9.1 in
Series: Use R Ser.
Item Width: 6.8 in
Format: Perfect