Bayesian Inference in Statistical Analysis
Author | : George E. P. Box |
Publisher | : John Wiley & Sons |
Total Pages | : 610 |
Release | : 2011-01-25 |
ISBN-10 | : 9781118031445 |
ISBN-13 | : 111803144X |
Rating | : 4/5 (44X Downloads) |
Download or read book Bayesian Inference in Statistical Analysis written by George E. P. Box and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.