Lecture Notes in Statistics

Robust Bayesian Analysis

Editors: Rios Insua, David, Ruggeri, Fabrizio (Eds.)

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About this book

Robust Bayesian analysis aims at overcoming the traditional objection to Bayesian analysis of its dependence on subjective inputs, mainly the prior and the loss. Its purpose is the determination of the impact of the inputs to a Bayesian analysis (the prior, the loss and the model) on its output when the inputs range in certain classes. If the impact is considerable, there is sensitivity and we should attempt to further refine the information the incumbent classes available, perhaps through additional constraints on and/ or obtaining additional data; if the impact is not important, robustness holds and no further analysis and refinement would be required. Robust Bayesian analysis has been widely accepted by Bayesian statisticians; for a while it was even a main research topic in the field. However, to a great extent, their impact is yet to be seen in applied settings. This volume, therefore, presents an overview of the current state of robust Bayesian methods and their applications and identifies topics of further in­ terest in the area. The papers in the volume are divided into nine parts covering the main aspects of the field. The first one provides an overview of Bayesian robustness at a non-technical level. The paper in Part II con­ cerns foundational aspects and describes decision-theoretical axiomatisa­ tions leading to the robust Bayesian paradigm, motivating reasons for which robust analysis is practically unavoidable within Bayesian analysis.

Table of contents (21 chapters)

  • Bayesian Robustness

    Berger, James O. (et al.)

    Pages 1-32

  • Topics on the Foundations of Robust Bayesian Analysis

    Insua, David Ríos (et al.)

    Pages 33-44

  • Global Bayesian Robustness for Some Classes of Prior Distributions

    Moreno, Elias

    Pages 45-70

  • Local Robustness in Bayesian Analysis

    Gustafson, Paul

    Pages 71-88

  • Global and Local Robustness Approaches: Uses and Limitations

    Sivaganesan, Siva

    Pages 89-108

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-1-4612-1306-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $179.00
price for USA
  • ISBN 978-0-387-98866-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Robust Bayesian Analysis
Editors
  • David Rios Insua
  • Fabrizio Ruggeri
Series Title
Lecture Notes in Statistics
Series Volume
152
Copyright
2000
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4612-1306-2
DOI
10.1007/978-1-4612-1306-2
Softcover ISBN
978-0-387-98866-5
Series ISSN
0930-0325
Edition Number
1
Number of Pages
XIII, 422
Number of Illustrations and Tables
6 b/w illustrations
Topics