Case Studies in Bayesian Statistics (Lecture Notes in Statistics, 83) - Softcover

Softcover

ISBN 10: 038794043X ISBN 13: 9780387940434

Publisher: Springer, 1993

Synopsis

The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to present several detailed examples of applications of Bayesian thinking, with an emphasis on the scientific or technological context of the problem being solved. The papers collected here were presented and discussed at a Workshop held at Carnegie-Mellon University, September 29 through October 1, 1991. There are five ma­ jor articles, each with two discussion pieces and a reply. These articles were invited by us following a public solicitation of abstracts. The problems they address are diverse, but all bear on policy decision-making. Though not part of our original design for the Workshop, that commonality of theme does emphasize the usefulness of Bayesian meth­ ods in this arena. Along with the invited papers were several additional commentaries of a general nature; the first comment was invited and the remainder grew out of the discussion at the Workshop. In addition there are nine contributed papers, selected from the thirty-four presented at the Workshop, on a variety of applications. This collection of case studies illustrates the ways in which Bayesian methods are being incorporated into statistical practice. The strengths (and limitations) of the approach become apparent through the examples.

About this title

From the Publisher:

This third volume of case studies presents detailed applications of Bayesian statistical analysis. Although the applications are from a variety of areas, the emphasis in this volume is on econometrics. The first two volumes have proved to be valuable references for statistical instructors and data analysts.

Review:

From the reviews:

TECHNOMETRICS

"...well written and can be appreciated by those with little biology background...In general, I found many of the papers collected in this book interesting...readers who are interested in applying Bayesian analysis in real case studies may find this book useful. One might consider using this book as supplementary material in graduate-level seminar courses on Bayesian data analysis."

Journal of the American Statistical Association, June 2004

"The volume as a whole illustrates the range of models that can now be fitted following the Markov chain Monte Carlo revolution, assess the behavior of posterior summaries under model misspecifications."

About this edition

• Publisher: Springer
• Publication date: 1993
• ISBN 10: 038794043X
• ISBN 13: 9780387940434
• Binding: Paperback
• Number of pages: 450
• Editor: Gatsonis Constantine, Hodges James S., Kass Robert E., Singpurwalla Nozer D.