Skip to main content
SpringerLink
Log in
Book cover

An Introduction to Bayesian Analysis

Theory and Methods

  • Textbook
  • © 2006

Overview

Authors:
  1. Jayanta K. Ghosh

    1. Department of Statistics, Purdue University, West Lafayette, USA
      Indian Statistical Institute, Kolkata, India

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Mohan Delampady

    1. Indian Statistical Institute, Bangalore, India

    View author publications

    You can also search for this author in PubMed   Google Scholar

  3. Tapas Samanta

    1. Indian Statistical Institute, Kolkata, India

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • No other such book is available in the market
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Texts in Statistics (STS)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 89.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

  1. Front Matter

    Pages I-XIII
    Download chapter PDF

  2. Statistical Preliminaries

    Pages 1-27

  3. Bayesian Inference and Decision Theory

    Pages 29-63

  4. Utility, Prior, and Bayesian Robustness

    Pages 65-97

  5. Large Sample Methods

    Pages 99-119

  6. Choice of Priors for Low-dimensional Parameters

    Pages 121-157

  7. Hypothesis Testing and Model Selection

    Pages 159-204

  8. Bayesian Computations

    Pages 205-237

  9. Some Common Problems in Inference

    Pages 239-254

  10. High-dimensional Problems

    Pages 255-288

  11. Some Applications

    Pages 289-302

  12. Back Matter

    Pages 303-352
    Download chapter PDF
Back to top

Keywords

About this book

Though there are many recent additions to graduate-level introductory books on Bayesian analysis, none has quite our blend of theory, methods, and ap­ plications. We believe a beginning graduate student taking a Bayesian course or just trying to find out what it means to be a Bayesian ought to have some familiarity with all three aspects. More specialization can come later. Each of us has taught a course like this at Indian Statistical Institute or Purdue. In fact, at least partly, the book grew out of those courses. We would also like to refer to the review (Ghosh and Samanta (2002b)) that first made us think of writing a book. The book contains somewhat more material than can be covered in a single semester. We have done this intentionally, so that an instructor has some choice as to what to cover as well as which of the three aspects to emphasize. Such a choice is essential for the instructor. The topics include several results or methods that have not appeared in a graduate text before. In fact, the book can be used also as a second course in Bayesian analysis if the instructor supplies more details. Chapter 1 provides a quick review of classical statistical inference. Some knowledge of this is assumed when we compare different paradigms. Following this, an introduction to Bayesian inference is given in Chapter 2 emphasizing the need for the Bayesian approach to statistics.

Reviews

From the reviews:

"This text provides a unique blend of theory, methods and applications that is suitable for a one-semester course in Bayesian analysis." C.M. O'Brien for Short Book Reviews of the ISI, December 2006

"The material of the book covers more than a one semester course and provides enough results for a second course. … the book is simultaneously useful for different readership groups. Instructors will get guidelines for preparing a course on Bayesian statistics … . Students will enjoy the excellently clear … style and the exercises at the end of each chapter. Practitioners will find plenty of classical and recent Bayesian methods. … I highly recommend the book to all readers who are interested in Bayesian statistics." (Friedrich Liese, Mathematical Reviews, Issue, 2007 g)

"This book, with its 10 chapters, represents a valuable introduction to Bayesian statistics and varies among theory, methods and applications. … The book’s material is invaluable, and is presented with clarity … . Each chapter’s topics are covered by various examples and many exercises. … gives a constructive approach to the statistical analysis based on Bayes’ formula. … So, it is strongly recommended to libraries and all who are interested in statistics." (Hassan S. Bakouch, Journal of Applied Statistics, Vol. 35 (3), 2008)

"Taken overall, the book should be recommended to a wide audience...as a source of interesting and mind-provoking information about Bayesian statistics. " ( ISCB News, 2008)

"Bayesian analysis have arrived. … This text offers one approach based on the pedagogic decision to ‘balance theory, methods, and applications.’ … The brief introduction to classical inference … provides a nice basis for the objective Bayesian treatment offered by the authors throughout the book. … this book appealing for classically trained statisticians. … Overall, I congratulate the authors for a largelysuccessful attempt to introduce true religion." (C. Shane Reese, Journal of the American Statistical Association, Vol. 103 (482), June, 2008)

"The book under review aims to contribute to existing graduate-level introductory texts on Bayesian analysis by providing an impressive blend of theory, methods, and applications. It consists of 10 chapters and 5 appendices." (Joseph Melamed, Zentralblatt MATH, Vol. 1135 (13), 2008)

"This book is an introduction to the theory and methods underlying Bayesian statistics written by three absolute experts on the field. It is primarily intended for graduate students taking a first course in Bayesian analysis or instructors preparing an introductory one-semester course on Bayesian analysis. … The book is written in a clear, relatively mathematical style … ." (Björn Bornkamp, Advances in Statistical Analysis, Issue 1, 2009)

"This book introduces the mathematical theory of Bayesian analysis along the statistical line of decision theory. … This book is intended as a graduate-level analysis of mathematical problems in Bayesian statistics and can in parts be used as textbook on Bayesian theory. … Overall, if I had to recommend a good book on new advancements of Bayesian statistics in the last decade from a theoretical decision point of view, I would recommend this book." (Wolfgang Polasek, Statistical Papers, Vol. 50, 2009)

Authors and Affiliations

  • Department of Statistics, Purdue University, West Lafayette, USA

    Jayanta K. Ghosh

  • Indian Statistical Institute, Kolkata, India

    Jayanta K. Ghosh, Tapas Samanta

  • Indian Statistical Institute, Bangalore, India

    Mohan Delampady

Bibliographic Information

  • Book Title: An Introduction to Bayesian Analysis

  • Book Subtitle: Theory and Methods

  • Authors: Jayanta K. Ghosh, Mohan Delampady, Tapas Samanta

  • Series Title: Springer Texts in Statistics

  • DOI: https://doi.org/10.1007/978-0-387-35433-0

  • Publisher: Springer New York, NY

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer-Verlag New York 2006

  • Hardcover ISBN: 978-0-387-40084-6Published: 27 July 2006

  • Softcover ISBN: 978-1-4419-2303-5Published: 19 November 2010

  • eBook ISBN: 978-0-387-35433-0Published: 03 July 2007

  • Series ISSN: 1431-875X

  • Series E-ISSN: 2197-4136

  • Edition Number: 1

  • Number of Pages: XIII, 354

  • Topics: Statistical Theory and Methods

Publish with us

Policies and ethics

Back to top

Search

Navigation