Bayesian Inference in Statistical Analysis / Edition 1

Bayesian Inference in Statistical Analysis / Edition 1

by George E. P. Box, George C. Tiao
     
 

ISBN-10: 0471574287

ISBN-13: 9780471574286

Pub. Date: 04/03/1992

Publisher: Wiley

Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution,

Overview

Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

Product Details

ISBN-13:
9780471574286
Publisher:
Wiley
Publication date:
04/03/1992
Series:
Wiley Classics Library Series, #40
Edition description:
Wiley Classics
Pages:
608
Product dimensions:
6.06(w) x 8.96(h) x 1.58(d)

Related Subjects

Table of Contents

Nature of Bayesian Inference.

Standard Normal Theory Inference Problems.

Bayesian Assessment of Assumptions: Effect of Non-Normality on Inferences About a Population Mean with Generalizations.

Bayesian Assessment of Assumptions: Comparison of Variances.

Random Effect Models.

Analysis of Cross Classification Designs.

Inference About Means with Information from More than One Source: One-Way Classification and Block Designs.

Some Aspects of Multivariate Analysis.

Estimation of Common Regression Coefficients.

Transformation of Data.

Tables.

References.

Indexes.

Customer Reviews

Average Review:

Write a Review

and post it to your social network

     

Most Helpful Customer Reviews

See all customer reviews >