Maximum Entropy and Bayesian Methods

1. Front Matter

   Pages i-xii

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2. Notes on Present Status and Future Prospects

   1. Notes on Present Status and Future Prospects

      • E. T. Jaynes

      Pages 1-13

3. Economics and Econometrics

   1. Front Matter

      Pages 15-15

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   2. Bayesian Methods and Entropy in Economics and Econometrics

      • Arnold Zellner

      Pages 17-31

   3. The Role of Priors in Active Bayesian Learning in the Sequential Statistical Decision Framework

      • Mahmoud A. El-Gamal

      Pages 33-38

   4. The Principle of Maximum Entropy and the Difference between Risk and Uncertainty

      • Christopher Grandy

      Pages 39-47

4. Astronomy and Astrophysics

   1. Front Matter

      Pages 49-49

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   2. Analysis of Lunar Occultation Data

      • W. P. Chen

      Pages 51-57

   3. The Photometric Accuracy of Astronomical Images Restored with the MEMSYS3 Code

      • J. G. Cohen

      Pages 59-65

   4. Computational Problems and Signal Processing in SETI

      • Stanley R. Deans, D. Kent Cullers, Richard Stauduhar

      Pages 67-75

5. General Physics

   1. Front Matter

      Pages 77-77

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   2. Maximum Entropy in Condensed Matter Theory

      • David Drabold, Gerald Jones

      Pages 79-92

   3. Entropy Maximization in Nuclear Physics

      • F. H. Fröhner

      Pages 93-107

   4. Applications of Maxent to Quantum Monte Carlo

      • Richard N. Silver, Devinderjit S. Sivia, James E. Gubernatis, Mark Jarrell

      Pages 109-125

   5. Maximum Entropy Applications in Radar

      • Glenn Heidbreder

      Pages 127-136

   6. The Application of Maximum Entropy Signal Processing to Ultrasonic Surface Parameterisation

      • P. F. Smith, M. A. Player

      Pages 137-146

   7. Steel Characterization using Bayesian Analysis of Barkhausen Noise

      • Louis Roemer, Nathan Ida

      Pages 147-152

   8. Bayesian Spectral Analysis of Reflectivity Data

      • D. S. Sivia, W. A. Hamilton, G. S. Smith

      Pages 153-159

   9. On the Assignment of Prior Expectation Values and a Geometric Means of Maximizing — Trρln ρ Constrained by Measured Expectation Values

      • Phillip R. Dukes, Everett G. Larson

      Pages 161-168

   10. The Evaluation and Predictive Properties of the “MemSys3” Algorithm

       • Anthony G. Ferrige, Michael J. Seddon

       Pages 169-180

The 10th International Workshop on Maximum Entropy and Bayesian Methods, MaxEnt 90, was held in Laramie, Wyoming from 30 July to 3 August 1990. This volume contains the scientific presentations given at that meeting. This series of workshops originated in Laramie in 1981, where the first three of what were to become annual workshops were held. The fourth meeting was held in Calgary. the fifth in Laramie, the sixth and seventh in Seattle, the eighth in Cambridge, England, and the ninth at Hanover, New Hampshire. It is most appropriate that the tenth workshop, occurring in the centennial year of Wyoming's statehood, was once again held in Laramie. The original purpose of these workshops was twofold. The first was to bring together workers from diverse fields of scientific research who individually had been using either some form of the maximum entropy method for treating ill-posed problems or the more general Bayesian analysis, but who, because of the narrow focus that intra-disciplinary work tends to impose upon most of us, might be unaware of progress being made by others using these same techniques in other areas. The second was to introduce to those who were somewhat aware of maximum entropy and Bayesian analysis and wanted to learn more, the foundations, the gestalt, and the power of these analyses. To further the first of these ends, presenters at these workshops have included workers from area. s as varied as astronomy, economics, environmenta.

• Statistica
• algorithm
• bayesian statistics
• information theory
• neural networks
• probability
• statistics

• Department of Physics and Astronomy, University of Wyoming, Laramie, USA

  W. T. Grandy, L. H. Schick

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