| 书目名称 | Markov Chains and Invariant Probabilities | | 编辑 | Onésimo Hernández-Lerma,Jean Bernard Lasserre | | 视频video | | | 概述 | Some of the results presented appear for the first time in book form.Emphasis on the role of expected occupation measures to study the long-run behavior of Markov chains on uncountable spaces | | 丛书名称 | Progress in Mathematics | | 图书封面 |  | | 描述 | 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). | | 出版日期 | Book 2003 | | 关键词 | Markov chain; ergodicity; mathematical methods in physics; probability measure; probability theory | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-0348-8024-4 | | isbn_softcover | 978-3-0348-9408-1 | | isbn_ebook | 978-3-0348-8024-4Series ISSN 0743-1643 Series E-ISSN 2296-505X | | issn_series | 0743-1643 | | copyright | Birkhäuser Verlag 2003 |
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发表于 2025-3-21 19:39:19
