Computing moments of first passage times to a subset of states in Markov chains
Date
2005Source Title
SIAM Journal on Matrix Analysis and Applications
Print ISSN
1095-7162 0895-4798
Publisher
SIAM
Volume
27
Issue
2
Pages
396 - 412
Language
English
Type
ArticleItem Usage Stats
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Abstract
This paper presents a relatively efficient and accurate method to compute the moments of first passage times to a subset of states in finite ergodic Markov chains. With the proposed method, the moment computation problem is reduced to the solution of a linear system of equations with the right-hand side governed by a novel recurrence for computing the higher-order moments. We propose using a form of the Grassmann-Taksar-Heyman (GTH) algorithm to solve these linear equations. Due to the form of the linear systems involved, the proposed method does not suffer from the drawbacks associated with GTH in a row-wise sparse implementation. © 2005 Society for Industrial and Applied Mathematics.
Keywords
First passage timesGrassmann-Taksar-Heyman algorithm
Markov chains
Mean
Moments
Unsafe states
Variance
Algorithms
Linear equations
Linear systems
Method of moments
Problem solving
First passage times
Grassmann-Taksar-Heyman algorithm
Mean
Moments
Unsafe states
Variance
Markov processes