An algorithm to compute the stochastically stable distribution of a perturbed Markov matrix
by Wicks, John R., Ph.D., BROWN UNIVERSITY, 2009, 210 pages; 3377227

Abstract:

Recently, some researchers have attempted to exploit state-aggregation techniques to compute stable distributions of high-dimensional Markov matrices (Gambin and Pokarowski, 2001). 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.
 
AdviserAmy Greenwald
SchoolBROWN UNIVERSITY
SourceDAI/B 70-10, p. , Dec 2009
Source TypeDissertation
SubjectsComputer science
Publication Number3377227
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