Maximum Entropy and Bayesian Methods in Applied Statistics: Proceedings of the Fourth Maximum Entropy Workshop University of Calgary, 1984

Maximum Entropy and Bayesian Methods in Applied Statistics: Proceedings of the Fourth Maximum Entropy Workshop University of Calgary, 1984

by James H. Justice
ISBN-10:
0521096030
ISBN-13:
9780521096034
Pub. Date:
01/11/2009
Publisher:
Cambridge University Press
ISBN-10:
0521096030
ISBN-13:
9780521096034
Pub. Date:
01/11/2009
Publisher:
Cambridge University Press
Maximum Entropy and Bayesian Methods in Applied Statistics: Proceedings of the Fourth Maximum Entropy Workshop University of Calgary, 1984

Maximum Entropy and Bayesian Methods in Applied Statistics: Proceedings of the Fourth Maximum Entropy Workshop University of Calgary, 1984

by James H. Justice

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Overview

This collection of papers by leading researchers in their respective fields contains contributions showing the use of the maximum entropy method in many of the fields in which it finds application. In the physical, mathematical and biological sciences it is often necessary to make inferences based on insufficient data. The problem of choosing one among the many possible conclusions or models which are compatible with the data may be resolved in a variety of ways. A particularly appealing method is to choose the solution which maximizes entropy in the sense that the conclusion or model honours the observed data but implies no further assumptions not warranted by the data. The maximum entropy principle has been growing in importance and acceptance in many fields, perhaps most notably statistical physics, astronomy, geophysics, signal processing, image analysis and physical chemistry. The papers included in this volume touch on most of the current areas of research activity and application, and will be of interest to research workers in all fields in which the maximum entropy method may be applied.

Product Details

ISBN-13: 9780521096034
Publisher: Cambridge University Press
Publication date: 01/11/2009
Pages: 332
Product dimensions: 6.70(w) x 9.40(h) x 0.80(d)

Table of Contents

1. Bayesian Methods: General Background E. T Jaynes; 2. Monkeys, Kangaroos, and N E. T Jaynes; 3. The Theory and Practice of the Maximum Entropy Formalism R. D. Levine; 4. Bayesian Non-Parametric Statistics Stephen F. Gull and John Fielden; 5. Generalized Entropies and the Maximum Entropy Principle J. Aczel and B. Forte; 6. The Probability of a Probability John F. Cyranski; 7. Prior Probabilities Revisited N. C Dalkey; 8. Band Extensions, Maximum Entropy and the Permanence Principle Robert L. Ellis, Israel Gohberg and David Lay; 9. Theory of Maximum Entropy Image Reconstruction John Skilling; 10. The Cambridge Maximum Entropy Algorithm John Skilling; 11. Maximum Entropy and the Moments Problem: Spectroscopic Applications C. G. Gray; 12. Maximum-Entropy Spectrum from a Non-Extendable Autocorrelation Function Paul F. Fougere; 13. Multichannel Maximum Entropy Spectral Analysis Using Least Squares Modelling P. A. Tyraskis; 14. Multichannel Relative-Entropy Spectrum Analysis Bruce R. Musicus and Rodney W. Johnson; 15. Maximum Entropy and the Earth's Density E. Rietsch; 16. Entropy and Some Inverse Problems in Exploration Seismology James H. Justice; 17. Principle of Maximum Entropy and Inverse Scattering Problems Ramarao Inguva and James Baker-Jarvis.
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