Advertisement

Case Studies in Bayesian Statistics

  • Constantine Gatsonis
  • James S. Hodges
  • Robert E. Kass
  • Nozer D. Singpurwalla

Part of the Lecture Notes in Statistics book series (LNS, volume 83)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Invited Papers

    1. Front Matter
      Pages xiii-xiii
    2. Richard W. Andrews, James O. Berger, Murray H. Smith
      Pages 1-77
    3. Anthony O’Hagan, Frank S. Wells
      Pages 118-162
    4. Adrian E. Raftery, Judith E. Zeh
      Pages 163-240
    5. Robert L. Wolpert, Laura J. Steinberg, Kenneth H. Reckhow
      Pages 241-293
  3. Final Discussion

    1. Front Matter
      Pages 295-295
    2. Thomas A. Louis
      Pages 297-301
    3. James O. Berger
      Pages 302-307
  4. Contributed Papers

    1. Front Matter
      Pages 309-309
    2. Ruth Etzioni, Bradley P. Carlin
      Pages 311-323
    3. Stuart Greene, Larry Wasserman
      Pages 337-350
    4. William S. Jewell, Shrane-Koung Chou
      Pages 351-361
    5. Frank Lad, Mark W. Brabyn
      Pages 362-376
    6. Mike West, Guoliang Cao
      Pages 416-428
  5. Back Matter
    Pages 429-439

About these proceedings

Introduction

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.

Keywords

bayesian statistics data analysis statistics

Editors and affiliations

  • Constantine Gatsonis
    • 1
  • James S. Hodges
    • 2
  • Robert E. Kass
    • 3
  • Nozer D. Singpurwalla
    • 4
  1. 1.Department of Health Care PolicyHarvard Medical SchoolBostonUSA
  2. 2.RANDSanta MonicaUSA
  3. 3.Department of StatisticsCarnegie-Mellon UniversityPittsburghUSA
  4. 4.Department of Operations ResearchThe George Washington UniversityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-2714-4
  • Copyright Information Springer-Verlag New York 1993
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-94043-4
  • Online ISBN 978-1-4612-2714-4
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site