An Algorithm to Compute the Stochastically Stable Distribution of a Perturbed Markov Matrix

Wicks, John Randolph

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Year:: 2009
Contributor:: Wicks, John Randolph (creator); Greenwald, Amy (director); Serrano, Roberto (reader); Centintemel, Ugur (reader); Brown University. Computer Science (sponsor)
Genre:: theses
Subject:: Markov chains; stochastic stability; state aggregation; Markov processes
Extent:: xvi, 193 p.
DOI: https://doi.org/10.7301/Z09Z93BN

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Abstract:: Recently, some researchers have attempted to exploit state-aggregation techniques to compute stable distributions of high-dimensional Markov matrices. While these researchers have devised an efficient, recursive algorithm, their results are only approximate. We improve upon past results by presenting a novel state aggregation technique, which we use to give the first (to our knowledge) scalable, exact algorithm for computing the stochastically stable distribution of a perturbed Markov matrix. Since it is not combinatorial in nature, our algorithm is computationally feasible even for high-dimensional models.
Notes:: Thesis (Ph.D.) -- Brown University (2009)

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Rights: In Copyright
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Citation

Wicks, John Randolph, "An Algorithm to Compute the Stochastically Stable Distribution of a Perturbed Markov Matrix" (2009). Computer Science Theses and Dissertations. Brown Digital Repository. Brown University Library. https://doi.org/10.7301/Z09Z93BN

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Computer Science Theses and Dissertations

Theses and Dissertations for the Computer Science department.
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