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A sharp lower bound for choosing the maximum of an independent sequence

Published online by Cambridge University Press:  09 December 2016

Pieter C. Allaart*
Affiliation:
University of North Texas
José A. Islas*
Affiliation:
University of North Texas
*
* Postal address: Department of Mathematics, University of North Texas, 1155 Union Circle #311430, Denton, TX 76203-5017, USA.
* Postal address: Department of Mathematics, University of North Texas, 1155 Union Circle #311430, Denton, TX 76203-5017, USA.
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Abstract

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In this paper we consider a variation of the full-information secretary problem where the random variables to be observed are independent but not necessary identically distributed. The main result is a sharp lower bound for the optimal win probability. Precisely, if X 1,...,X n are independent random variables with known continuous distributions and V n (X 1,...,Xn ):=supτℙ(X τ=M n ), where M n ≔max{X 1,...,X n } and the supremum is over all stopping times adapted to X 1,...,X n then V n (X 1,...,X n )≥(1-1/n)n-1, and this bound is attained. The method of proof consists in reducing the problem to that of a sequence of random variables taking at most two possible values, and then applying Bruss' sum-the-odds theorem, Bruss (2000). In order to obtain a sharp bound for each n, we improve Bruss' lower bound, Bruss (2003), for the sum-the-odds problem.

Information

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2016