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Approximating a Cumulative Distribution Function by Generalized Hyperexponential Distributions

Published online by Cambridge University Press:  27 July 2009

Jihong Ou
Affiliation:
Department of Decision Sciences, National University of Singapore, 10 Kent Ridge Crescent, Singapore, 11926O
Jingwen Li
Affiliation:
Department of Decision Sciences, National University of Singapore, 10 Kent Ridge Crescent, Singapore, 11926O
Süleyman Özekici
Affiliation:
Department of Industrial Engineering, Boḡaziçi University, 80815 Bebek-lstanbul, Turkey

Abstract

Recent developments in stochastic modeling show that enormous analytical advantages can be gained if a general cumulative distribution function (c.d.f.) can be approximated by generalized hyperexponential distributions. In this paper, we introduce a procedure to explicitly construct such approximations of an arbitrary c.d.f. Although our approach can be used in different types of stochastic models, the main motivation comes from queueing theory in obtaining approximations of the idle-period distribution and other performance measures in GI/G/1 queues.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1997

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