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Bayesian model selection and statist...

Ando, Tomohiro.

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Bayesian model selection and statistical modeling /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Bayesian model selection and statistical modeling // Tomohiro Ando.
Author:	Ando, Tomohiro.
Published:	Boca Raton, FL :CRC Press, : 2010.,
Description:	xiv, 286 p. :ill. ;25 cm.
Subject:	Bayesian statistical decision theory. -
ISBN:	9781439836149 (hbk.) :

Bayesian model selection and statistical modeling /
Ando, Tomohiro.

Bayesian model selection and statistical modeling /Tomohiro Ando. - Boca Raton, FL :CRC Press,2010. - xiv, 286 p. :ill. ;25 cm. - Statistics : textbooks and monographs.

Includes bibliographical references (p. 265-284) and index.

"Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation. The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provides a theoretical basis for the analysis of these criteria. In addition, the author discusses how Bayesian model averaging can simultaneously treat both model and parameter uncertainties. Selecting and constructing the appropriate statistical model significantly affect the quality of results in decision making, forecasting, stochastic structure explorations, and other problems. Helping you choose the right Bayesian model, this book focuses on the framework for Bayesian model selection and includes practical examples of model selection criteria."--Publisher's description.

ISBN: 9781439836149 (hbk.) :UK59.99

LCCN: 2010017141Subjects--Topical Terms:

551404
Bayesian statistical decision theory.

LC Class. No.: QA279.5 / .A55 2010

Dewey Class. No.: 519.5/42

Bayesian model selection and statistical modeling /
LDR:02026cam 2200217 a 4500 001 1267691
005 20120906150607.0
008 120911s2010 flua b 001 0 eng
010 $a 2010017141
020 $a 9781439836149 (hbk.) : $c UK59.99
020 $a 1439836140 (hbk.)
035 $a AS-BW-101-N-06
040 $a DLC $c DLC $d YDX $d BTCTA $d YDXCP $d CDX $d BWX $d VRC $d UBY $d DLC
050 0 0 $a QA279.5 $b .A55 2010
082 0 0 $a 519.5/42 $2 22
090 $a QA/279.5/.A55/2010//////W0161217
100 1 $a Ando, Tomohiro. $3 1535965
245 1 0 $a Bayesian model selection and statistical modeling / $c Tomohiro Ando.
260 # $a Boca Raton, FL : $b CRC Press, $c 2010.
300 $a xiv, 286 p. : $b ill. ; $c 25 cm.
490 1 0 $a Statistics : textbooks and monographs
504 $a Includes bibliographical references (p. 265-284) and index.
520 # $a "Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation. The author shows how to implement a variety of Bayesian inference using R and sampling methods, such as Markov chain Monte Carlo. He covers the different types of simulation-based Bayesian model selection criteria, including the numerical calculation of Bayes factors, the Bayesian predictive information criterion, and the deviance information criterion. He also provides a theoretical basis for the analysis of these criteria. In addition, the author discusses how Bayesian model averaging can simultaneously treat both model and parameter uncertainties. Selecting and constructing the appropriate statistical model significantly affect the quality of results in decision making, forecasting, stochastic structure explorations, and other problems. Helping you choose the right Bayesian model, this book focuses on the framework for Bayesian model selection and includes practical examples of model selection criteria."--Publisher's description.
650 # 0 $a Bayesian statistical decision theory. $3 551404
650 # 0 $a Mathematical statistics. $3 516858
650 # 0 $a Mathematical models. $3 522882