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      Computing moments of first passage times to a subset of states in Markov chains

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      Author(s)
      Dayar T.
      Akar, N.
      Date
      2005
      Source 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
      Article
      Item 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 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
      Permalink
      http://hdl.handle.net/11693/23797
      Published Version (Please cite this version)
      http://dx.doi.org/10.1137/S0895479804442462
      Collections
      • Department of Computer Engineering 1561
      • Department of Electrical and Electronics Engineering 4011
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