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Optimal selection based on relative ranks of a sequence by ties

Published online by Cambridge University Press:  01 July 2016

Gregory Campbell
Gregory Campbell*
Affiliation:
Purdue University
*
∗ Present address: Division of Computer Research and Technology, National Institutes of Health, Bethesda, MD 20205, U.S.A.
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Abstract

The optimal selection of a maximum of a sequence with the possibility of ties is considered. The object is to examine each observation in the sequence of known length n and, based only on the relative rank among predecessors, either to stop and select it as a maximum or to continue without recall. Rules which maximize the probability of correctly selecting a maximum from a sequence with ties are investigated. These include rules which randomly break ties, rules which discard tied observations, and minimax rules based on the atoms of a discrete distribution function. If the sequence is random from F, a random distribution function from a Dirichlet process prior with non-atomic parameter, optimal rules are developed. The limiting behavior of these rules is studied and compared with other rules. The selection of the parameter of the Dirichlet process regulates the ties.

Keywords

BEST CHOICE PROBLEMDIRICHLET PROCESS PRIOROPTIMAL STOPPINGRELATIVE RANKSSECRETARY PROBLEM

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 16 , Issue 1 , March 1984, pp. 131 - 146
Copyright
Copyright © Applied Probability Trust 1984 

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Footnotes

Research supported in part by National Science Foundation Grant MCS78–02895.

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