Computing moments of first passage times to a subset of states in Markov chains
Date
2005
Authors
Dayar T.
Akar, N.
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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.
Source Title
SIAM Journal on Matrix Analysis and Applications
Publisher
SIAM
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Keywords
First passage times, Grassmann-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
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English