A generalized maximum entropy principle for decision analysis
By: by Marlin U. Thomas
Contributors: Naval Postgraduate School (U.S.)
Publisher: Naval Postgraduate School
Published: 1977
Place of publication: Monterey, Calif
Language: eng
Number of pages: 21
Subjects: Bayesian statistical decision theory; Statistical decision
Description: A generalized maximum entropy principle is described for dealing with decision problems involving uncertainty but with some prior knowledge about the probability space corresponding to nature. This knowledge about the probabilistic structure is expressed through known bounds on event probabilities and moments, which is incorporated into a nonlinear programming problem. The solution provides a maximum entropy distribution which is then used in treating the decision problem as one involving risk. An example application is described that involves the selection of oil spill recovery systems for inland harbor regions. Other areas of application are identified and tables of some maximum entropy distributions resulting from a variety of moment constraints are provided.
Notes: Title from cover.

"April 1977"--Cover.

"NPS-55-77-20"--Cover.

Includes bibliographical references (p. 18-19)

"Approved for public release; distribution unlimited"--Cover.

Technical report; 1977.