Constrained noninformative priors
Constrained noninformative priors
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.
- University of North Texas United States
Distribution Functions, 330, Computers, Entropy, Distribution, 99 Mathematics, Risk Assessment, Management, Miscellaneous, Law, Information Science, Probability
Distribution Functions, 330, Computers, Entropy, Distribution, 99 Mathematics, Risk Assessment, Management, Miscellaneous, Law, Information Science, Probability
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