Practical Nonparametric and Semiparametric Bayesian Statistics

  • Dipak Dey
  • Peter Müller
  • Debajyoti Sinha

Part of the Lecture Notes in Statistics book series (LNS, volume 133)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. I Dirichlet And Related Processes

    1. Michael D. Escobar, Mike West
      Pages 1-22
    2. Michael A. Newton, Fernando A. Quintana, Yunlei Zhang
      Pages 45-61
    3. Joseph G. Ibrahim, Kenneth P. Kleinman
      Pages 89-114
    4. Pantelis K. Vlachos, Alan E. Gelfand
      Pages 115-132
  3. II Modeling Random Functions

  4. III Lévy And Related Processes

    1. Debajyoti Sinha, Dipak K. Dey
      Pages 195-211
    2. Purushottam W. Laud, Paul Damien, Adrian F. M. Smith
      Pages 213-225
    3. Robert L. Wolpert, Katja Ickstadt
      Pages 227-242
  5. IV Prior Elicitation And Asymptotic Properties

    1. Joseph G. Ibrahim, Debajyoti Sinha
      Pages 273-292
  6. V Case Studies

    1. Katja Ickstadt, Robert L. Wolpert, Xuedong Lu
      Pages 305-322
    2. Peter Müller, Gary Rosner
      Pages 323-337
    3. Liping Liu, Elja Arjas
      Pages 339-353
  7. Back Matter
    Pages 370-371

About this book


A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.


Survival analysis bayesian statistics linear optimization neural networks statistics

Editors and affiliations

  • Dipak Dey
    • 1
  • Peter Müller
    • 2
  • Debajyoti Sinha
    • 3
  1. 1.Department of StatisticsUniversity of ConnecticutStorrsUSA
  2. 2.ISDSDuke UniversityDurhamUSA
  3. 3.Department of MathematicsUniversity of New HampshireDurhamUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York, Inc. 1998
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98517-6
  • Online ISBN 978-1-4612-1732-9
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site