Markov Chains and Invariant Probabilities

Onésimo Hernández-Lerma|Jean B. Lasserre

ISBN 10: 3764370009 / ISBN 13: 9783764370008

Editore: Birkhäuser Basel, 2003

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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Some of the results presented appear for the first time in book formEmphasis on the role of expected occupation measures to study the long-run behavior of Markov chains on uncountable spacesThis book is about discrete-time, time-homoge. Codice articolo 5279559

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Titolo: Markov Chains and Invariant Probabilities

Casa editrice: Birkhäuser Basel

Data di pubblicazione: 2003

Legatura: Rilegato

Condizione: New

Descrizione articolo

Riassunto:

This book is about discrete-time, time-homogeneous, Markov chains (Mes) and their ergodic behavior. To this end, most of the material is in fact about stable Mes, by which we mean Mes that admit an invariant probability measure. To state this more precisely and give an overview of the questions we shall be dealing with, we will first introduce some notation and terminology. Let (X,B) be a measurable space, and consider a X-valued Markov chain ~. = {~k' k = 0, 1, ... } with transition probability function (t.pJ.) P(x, B), i.e., P(x, B) := Prob (~k+1 E B I ~k = x) for each x E X, B E B, and k = 0,1, .... The Me ~. is said to be stable if there exists a probability measure (p.m.) /.l on B such that (*) VB EB. /.l(B) = Ix /.l(dx) P(x, B) If (*) holds then /.l is called an invariant p.m. for the Me ~. (or the t.p.f. P).

Recensione:

"It should be stressed that an important part of the results presented is due to the authors. . . . In the reviewer's opinion, this is an elegant and most welcome addition to the rich literature of Markov processes."

--MathSciNet