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Smallest-fit selection of random sizes under a sum constraint: weak convergence and moment comparisons

Part of:Limit theoremsStochastic processesOperations research and management science

Published online by Cambridge University Press:  01 July 2016

Frans A. Boshuizen and
Robert P. Kertz
Frans A. Boshuizen*
Affiliation:
ING Bank Amsterdam
Robert P. Kertz*
Affiliation:
Georgia Institute of Technology
*
∗ Postal address: ING Bank Amsterdam, The Netherlands.
∗∗ Postal address: School of Mathematics, Georgia Institute of Technology, Atlanta, GA 30332-0160, USA.
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Abstract

In this paper, in work strongly related with that of Coffman et al. [5], Bruss and Robertson [2], and Rhee and Talagrand [15], we focus our interest on an asymptotic distributional comparison between numbers of ‘smallest’ i.i.d. random variables selected by either on-line or off-line policies. Let X 1,X 2,… be a sequence of i.i.d. random variables with distribution function F(x), and let X 1,n ,…,X n,n be the sequence of order statistics of X 1,…,X n . For a sequence (c n )n≥1 of positive constants, the smallest fit off-line counting random variable is defined by N e (c n ) := max {j ≤ n : X 1,n + … + X j,n ≤ c n }. The asymptotic joint distributional comparison is given between the off-line count N e (c n ) and on-line counts N n τ for ‘good’ sequential (on-line) policies τ satisfying the sum constraint ∑j≥1X τ j I (τj ≤n) ≤ c n . Specifically, for such policies τ, under appropriate conditions on the distribution function F(x) and the constants (c n )n≥1, we find sequences of positive constants (B n )n≥1, (Δn )n≥1 and (Δ'n )n≥1 such that

for some non-degenerate random variables W and W'. The major tools used in the paper are convergence of point processes to Poisson random measure and continuous mapping theorems, strong approximation results of the normalized empirical process by Brownian bridges, and some renewal theory.

Keywords

Joint convergence in distributionextreme sumsorder statisticsthreshold strategiescounting r.v.sPoisson random measurescontinuous mapping principlestrong approximationsBrownian bridgeon-line vs off-line strategies

MSC classification

Primary:60G40: Stopping times; optimal stopping problems; gambling theory60G70: Extreme value theory; extremal processes
Secondary:60F05: Central limit and other weak theorems60F15: Strong theorems60G55: Point processes90B50: Management decision making, including multiple objectives

Information

Type
General Applied Probability
Information
Advances in Applied Probability , Volume 31 , Issue 1 , March 1999, pp. 178 - 198
Copyright
Copyright © Applied Probability Trust 1999 

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