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Constrained noninformative priors

By C.L. Atwood

Abstract

The Jeffreys noninformative prior distribution for a single unknown parameter is the distribution corresponding to a uniform distribution in the transformed model where the unknown parameter is approximately a location parameter. To obtain a prior distribution with a specified mean but with diffusion reflecting great uncertainty, a natural generalization of the noninformative prior is the distribution corresponding to the constrained maximum entropy distribution in the transformed model. Examples are given

Topics: Probability, Entropy, 99 Mathematics, Computers, Information Science, Management, Law, Miscellaneous, Distribution Functions, Risk Assessment, Distribution
Publisher: EG & G, Inc.
Year: 1994
DOI identifier: 10.2172/43783
OAI identifier:
Provided by: UNT Digital Library
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