Onesimo Hernandez-Lerma, Jean B. Lasserre

Markov Chains and Invariant Probabilities

• Broschiertes Buch

Produktbeschreibung

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).

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Produktdetails

• Progress in Mathematics .211
• Verlag: Birkhäuser / Birkhäuser Basel / Springer, Basel
• Artikelnr. des Verlages: 978-3-0348-9408-1
• Softcover reprint of the original 1st ed. 2003
• Seitenzahl: 228
• Erscheinungstermin: 23. Oktober 2012
• Englisch
• Abmessung: 235mm x 155mm x 13mm
• Gewicht: 374g
• ISBN-13: 9783034894081
• ISBN-10: 3034894082
• Artikelnr.: 39523044

Inhaltsangabe

1 Preliminaries.- 1.1 Introduction.- 1.2 Measures and Functions.- 1.3 Weak Topologies.- 1.4 Convergence of Measures.- 1.5 Complements.- 1.6 Notes.- I Markov Chains and Ergodicity.- 2 Markov Chains and Ergodic Theorems.- 3 Countable Markov Chains.- 4 Harris Markov Chains.- 5 Markov Chains in Metric Spaces.- 6 Classification of Markov Chains via Occupation Measures.- II Further Ergodicity Properties.- 7 Feller Markov Chains.- 8 The Poisson Equation.- 9 Strong and Uniform Ergodicity.- III Existence and Approximation of Invariant Probability Measures.- 10 Existence of Invariant Probability Measures.- 11 Existence and Uniqueness of Fixed Points for Markov Operators.- 12 Approximation Procedures for Invariant Probability Measures.

Rezensionen

"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