Posted by **AvaxGenius** at Feb. 10, 2017

English | PDF | 438 Pages | 2017 | ISBN : 9811033064 | 10.02 MB

This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications.

Posted by **roxul** at June 9, 2016

English | ISBN: 1439884676 | 2016 | 480 pages | PDF | 13 MB

Posted by **libr** at Jan. 15, 2016

English | 2012 | ISBN: 1584889195 | ISBN-13: 9781584889199 | 427 pages | PDF | 4,8 MB

Posted by **nebulae** at Oct. 22, 2015

English | 2012 | ISBN: 1119941822 | 598 pages | PDF | 11,8 MB

Posted by **nebulae** at July 21, 2015

English | ISBN: 142008285X | 2011 | 544 pages | PDF | 5 MB

Posted by **BUGSY** at May 21, 2015

English | May 27, 2010 | ISBN: 1439836140 | 300 Pages | PDF | 5 MB

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…

Posted by **interes** at Feb. 8, 2015

English | 2012 | ISBN: 1584889195 | ISBN-13: 9781584889199 | 427 pages | PDF | 4,8 MB

Posted by **AlenMiler** at Oct. 15, 2014

Springer; 2001 edition | August 20, 2001 | English | ISBN: 1852334592 | 224 pages | PDF | 11 MB

Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice.

Posted by **ChrisRedfield** at Aug. 25, 2014

Published: 2013-12-04 | ISBN: 1461487749 | PDF | 400 pages | 6 MB

Posted by **interes** at May 30, 2014

English | 2010 | ISBN-10: 1439836140 | 300 pages | PDF | 6 MB

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.