Maximum Entropy and Bayesian Methods in Applied. Justice<|

Cambridge University Press

Maximum Entropy and Bayesian Methods in Applied StatisticsProceedings of the Fourth Maximum Entropy Workshop University of Calgary, 1984\nAuthor(s): James H. Justice\nFormat: Paperback\nPublisher: Cambridge University Press, United Kingdom\nImprint: Cambridge University Press\nISBN-13: 9780521096034, 978-0521096034\nSynopsis\nThis 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 .