Introduction

With Bayesian statistics rapidly becoming accepted as a way to solve applied statistical problems, the need for a comprehensive, up-to-date source on the latest advances in this field has arisen.

Content Overview

Presenting the basic theory of a large variety of linear models from a Bayesian viewpoint, Bayesian Analysis of Linear Models fills this need. Plus, this definitive volume contains something traditional—a review of Bayesian techniques and methods of estimation, hypothesis testing, and forecasting as applied to the standard populations ...

Innovative Approaches

Something innovative—a new approach to mixed models and models not generally studied by statisticians such as linear dynamic systems and changing parameter models ...

Practical Features

And something practical—clear graphs, easy-to-understand examples, end-of-chapter problems, numerous references, and a distribution appendix.

Target Audience

Comprehensible, unique, and in-depth, Bayesian Analysis of Linear Models is the definitive monograph for statisticians, econometricians, and engineers. In addition, this text is ideal for students in graduate-level courses such as linear models, econometrics, and Bayesian inference.