Bounds and approximations for continuous-time Markovian transition probabilities and large systems

被引:1
|
作者
Mercier, Sophie [1 ]
机构
[1] Univ Marne La Vallee, Lab Anal & Math Appl, CNRS, UMR 8050, F-77454 Marne La Vallee 2, France
关键词
Markov processes; numerical bounds and approximations; time-dependent quantities; reliability;
D O I
10.1016/j.ejor.2006.12.036
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
We propose new bounds and approximations for the transition probabilities of a continuous-time Markov process with finite but large state-space. The bounding and approximating procedures have been exposed in another paper [S. Mercier, Numerical bounds for semi-Markovian quantities and applications to reliability, in revision for Methodology and Computing in Applied Probability] in the more general context of a continuous-time semi-Markov process with countable state-space. Such procedures are here specialized to the Markovian finite case, leading to much simpler algorithms. The aim of this paper is to test such algorithms versus other algorithms from the literature near from ours, such as forward Euler approximation, external uniformization and a finite volume method from [C. Cocozza-Thivent, R. Eymard, Approximation of the marginal distributions of a semi-Markov process using a finite volume scheme, ESAIM: M2AN 38(5) (2004) 853-875]. (c) 2007 Elsevier B.V. All rights reserved.
引用
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页码:216 / 234
页数:19
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