Maximum-Entropy and Bayesian Methods in Science and Engineering

Volume 2: Applications

  • Gary J. Erickson
  • C. Ray Smith

Part of the Fundamental Theories of Physics book series (FTPH, volume 31-32)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Stanley R. Deans
    Pages 1-17
  3. David Hestenes
    Pages 19-32
  4. A. K. Rajagopal, P. J. Lin-Chung, S. Teitler
    Pages 83-88
  5. L. H. Schick
    Pages 89-103
  6. A. K. Rajagopal, S. Teitler
    Pages 121-126
  7. Thomas Dana Schneider
    Pages 147-154
  8. K. L. Ngai, A. K. Rajagopal, S. Teitler
    Pages 363-369
  9. S. A. Trugman
    Pages 371-379
  10. John H. Root, P. A. Egelstaff, B. G. Nickel
    Pages 395-407
  11. Keith H. Norsworthy, Paul N. Michels
    Pages 409-420
  12. Back Matter
    Pages 435-436

About this book


This volume has its origin in the Fifth, Sixth and Seventh Workshops on "Maximum-Entropy and Bayesian Methods in Applied Statistics", held at the University of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987. It was anticipated that the proceedings of these workshops would be combined, so most of the papers were not collected until after the seventh workshop. Because most of the papers in this volume are in the nature of advancing theory or solving specific problems, as opposed to status reports, it is believed that the contents of this volume will be of lasting interest to the Bayesian community. The workshop was organized to bring together researchers from different fields to critically examine maximum-entropy and Bayesian methods in science and engineering as well as other disciplines. Some of the papers were chosen specifically to kindle interest in new areas that may offer new tools or insight to the reader or to stimulate work on pressing problems that appear to be ideally suited to the maximum-entropy or Bayesian method. These workshops and their proceedings could not have been brought to their final form without the support or help of a number of people.


Estimator Fitting Information Likelihood Maximum entropy method Switch Variance best fit entropy production statistics

Editors and affiliations

  • Gary J. Erickson
    • 1
  • C. Ray Smith
    • 2
  1. 1.Department of Electrical EngineeringSeattle UniversitySeattleUSA
  2. 2.Advanced Sensors Directorate Research, Development and Engineering CenterUS Army Missile CommandRedstone ArsenalUSA

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media B.V. 1988
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-9056-8
  • Online ISBN 978-94-010-9054-4
  • Buy this book on publisher's site