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On a family of prior distributions for a class of Bayesian search models

Part of: Decision theory Stochastic processes

Published online by Cambridge University Press:  01 July 2016

K. D. Glazebrook
K. D. Glazebrook*
Affiliation:
University of Newcastle upon Tyne
*
∗ Postal address: Department of Mathematics and Statistics, The University, Newcastle upon Tyne NE1 7RU, UK.
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Abstract

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We propose a two-parameter family of conjugate prior distributions for the number of undiscovered objects in a class of Bayesian search models. The family contains the one-parameter Euler and Heine families as special cases. The two parameters may be interpreted respectively as an overall success rate and a rate of depletion of the source of objects. The new family gives enhanced flexibility in modelling.

Keywords

BAYES SEQUENTIAL DECISION RULEGITTINS INDEXOPTIMAL STOPPINGSEARCH MODELS

MSC classification

Primary: 62C10: Bayesian problems; characterization of Bayes procedures
Secondary: 60G40: Stopping times; optimal stopping problems; gambling theory
Type
Letter to the Editor
Information
Advances in Applied Probability , Volume 25 , Issue 3 , September 1993 , pp. 714 - 716
Copyright
Copyright © Applied Probability Trust 1993 

References

Bather, J. A. (1992) Search models. J. Appl. Prob. 29, 605–615.Google Scholar
Benkherouf, L. and Bather, J. A. (1988) Oil exploration: sequential decisions in the face of uncertainty. J. Appl. Prob. 25, 529–543.Google Scholar
Benkherouf, L., Glazebrook, K. D. and Owen, R. W. (1992) Gittins indices and oil exploration. J. R. Statist. Soc. B54, 229–241.Google Scholar
Kemp, A. W. (1992) Heine-Euler extensions of the Poisson distribution. Commun. Statist. Theory Meth. 21, 571–588.Google Scholar