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dc.contributor.authorHunter, JJ
dc.date.accessioned2012-01-19T22:06:14Z
dc.date.available2012-01-19T22:06:14Z
dc.date.copyright2011-12-15
dc.date.issued2012-01-20
dc.identifier.citationLectures on Matrix and Graph Methods, Manipal Univ Press Eds R.B. Bapat, S.Kirkland, K.M. Prasad, S. Puntanen, pp 61-89, (2012)
dc.identifier.urihttp://hdl.handle.net/10292/3278
dc.description.abstractIn many stochastic models a Markov chain is present either directly or indirectly through some form of embedding. The analysis of many problems of interest associated with these models, eg. stationary distributions, moments of first passage time distributions and moments of occupation time random variables, often requires the solution of a system of linear equations involving I – P, where P is the transition matrix of a finite, irreducible, discrete time Markov chain. Generalized matrix inverses play an important role in the solution of such singular sets of equations. In this presentation we survey the application of generalized inverses to the aforementioned problems focussing primarily on Markov chains.
dc.publisherManipal Univ Press/arXiv
dc.relation.urihttp://arxiv.org/abs/1112.3404
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation).
dc.titleThe derivation of Markov Chain Properties using Generalized Matrix Inverses
dc.typeBook Chapter
dc.rights.accessrightsOpenAccess


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