Maximum Entropy and Bayesian Methods in Applied Statistics by James H. Justice
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Maximum Entropy and Bayesian Methods in Applied Statistics
By James H. Justice

Maximum Entropy and Bayesian Methods in Applied Statistics

Proceedings of the Fourth Maximum Entropy Workshop University of Calgary, 1984

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Format: Paperback

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Maximum Entropy and Bayesian Methods in Applied Statistics by James H. Justice

Book Description

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.

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Book Details

ISBN: 9780521096034
ISBN-10: 0521096030
Format: Paperback
(244mm x 170mm x 18mm)
Pages: 332
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 11-Jan-2009
Country of Publication: United Kingdom

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