ABSTRACT

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

chapter 1|12 pages

Introduction

chapter 2|30 pages

Introduction to Bayesian analysis

chapter 3|20 pages

Asymptotic approach for Bayesian inference

chapter 5|68 pages

Bayesian approach for model selection

chapter 7|36 pages

Various Bayesian model selection criteria

chapter 8|22 pages

Theoretical development and comparisons

chapter 9|8 pages

Bayesian model averaging