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Combinatorial approaches to Monte Carlo estimation of network lifetime distribution
Author(s) -
Gertsbakh I.,
Shpungin Y.
Publication year - 2004
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.514
Subject(s) - monte carlo method , computer science , distribution (mathematics) , mathematical optimization , estimation , statistical physics , mathematics , statistics , engineering , physics , mathematical analysis , systems engineering
Abstract The purpose of this paper is estimating the lifetime distribution for two types of dynamic networks. The first one is a network, with edges existing in time, which may be erased independently of each other. The second one is a network with renewable edges. We consider effective Monte Carlo methods based on combinatorial approaches which were suggested earlier for estimating parameters of static networks. Copyright © 2004 John Wiley & Sons, Ltd.