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On the Method of Pure Truncation for Approximating Stationary Probabilities

dc.contributor.authorStewart, G. W.en_US
dc.description.abstractThis paper is concerned with approximating the leading components of the stationary vector of a semi-infinite discrete markov chain. The most widely treated method extracts a leading principal submatrix from the matrix of transition probabilities, adjusts its elements so that it becomes stochastic, and takes the stationary vector of the result as the approximation. In this paper, the consequences of taking the normalized Perron vector of the unadjusted matrix as the approximation are explored. Error bounds are derived, and it is shown that the adjusted and unadjusted methods are approximations to one another. (UMIACS-TR-2003-65)en_US
dc.format.extent195580 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4496en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2003-65en_US
dc.titleOn the Method of Pure Truncation for Approximating Stationary Probabilitiesen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US

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