Lecture Notes in Statistics

Bayesian Inference in Wavelet-Based Models

Editors: Müller, Peter, Vidakovic, Brani (Eds.)

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About this book

This volume presents an overview of Bayesian methods for inference in the wavelet domain. The papers in this volume are divided into six parts: The first two papers introduce basic concepts. Chapters in Part II explore different approaches to prior modeling, using independent priors. Papers in the Part III discuss decision theoretic aspects of such prior models. In Part IV, some aspects of prior modeling using priors that account for dependence are explored. Part V considers the use of 2-dimensional wavelet decomposition in spatial modeling. Chapters in Part VI discuss the use of empirical Bayes estimation in wavelet based models. Part VII concludes the volume with a discussion of case studies using wavelet based Bayesian approaches. The cooperation of all contributors in the timely preparation of their manuscripts is greatly recognized. We decided early on that it was impor­ tant to referee and critically evaluate the papers which were submitted for inclusion in this volume. For this substantial task, we relied on the service of numerous referees to whom we are most indebted. We are also grateful to John Kimmel and the Springer-Verlag referees for considering our proposal in a very timely manner. Our special thanks go to our spouses, Gautami and Draga, for their support.

Table of contents (23 chapters)

  • An Introduction to Wavelets

    Vidakovic, Brani (et al.)

    Pages 1-18

  • Spectral View of Wavelets and Nonlinear Regression

    Marron, J. S.

    Pages 19-32

  • Bayesian Approach to Wavelet Decomposition and Shrinkage

    Abramovich, Felix (et al.)

    Pages 33-50

  • Some Observations on the Tractability of Certain Multi-Scale Models

    Kolaczyk, Eric D.

    Pages 51-66

  • Bayesian Analysis of Change-Point Models

    Ogden, R. Todd (et al.)

    Pages 67-82

Buy this book

eBook $129.00
price for USA (gross)
  • ISBN 978-1-4612-0567-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $169.00
price for USA
  • ISBN 978-0-387-98885-6
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Bayesian Inference in Wavelet-Based Models
Editors
  • Peter Müller
  • Brani Vidakovic
Series Title
Lecture Notes in Statistics
Series Volume
141
Copyright
1999
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4612-0567-8
DOI
10.1007/978-1-4612-0567-8
Softcover ISBN
978-0-387-98885-6
Series ISSN
0930-0325
Edition Number
1
Number of Pages
XIV, 396
Topics