Markov Chains and Invariant Probabilities
Hernandez-Lerma, Onesimo; Lasserre, Jean-Bernard
ISBN 10: 3034894082 ISBN 13: 9783034894081
Published by Springer Basel, 2012
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About this Item
Description:
Series: Progress in Mathematics. Num Pages: 208 pages, biography. BIC Classification: KJT; PBT; PHU. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 12. Weight in Grams: 355. . 2012. Softcover reprint of the original 1st ed. 2003. Paperback. . . . . Books ship from the US and Ireland. Seller Inventory # V9783034894081
Synopsis:
This book concerns discrete-time homogeneous Markov chains that admit an invariant probability measure. The main objective is to give a systematic, self-contained presentation on some key issues about the ergodic behavior of that class of Markov chains. These issues include, in particular, the various types of convergence of expected and pathwise occupation measures, and ergodic decompositions of the state space.
From the Back Cover:
This book concerns discrete-time homogeneous Markov chains that admit an invariant probability measure. The main objective is to give a systematic, self-contained presentation on some key issues about the ergodic behavior of that class of Markov chains. These issues include, in particular, the various types of convergence of expected and pathwise occupation measures, and ergodic decompositions of the state space. Some of the results presented appear for the first time in book form. A distinguishing feature of the book is the emphasis on the role of expected occupation measures to study the long-run behavior of Markov chains on uncountable spaces.
The intended audience are graduate students and researchers in theoretical and applied probability, operations research, engineering and economics.
"About this title" may belong to another edition of this title.
Bibliographic Details
Title: Markov Chains and Invariant Probabilities
Publisher: Springer Basel
Publication Date: 2012
Binding: Soft cover
Condition: New
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Markov Chains and Invariant Probabilities
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Condition: New. 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. Seller Inventory # 4319225
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Markov Chains and Invariant Probabilities
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Birkhäuser Basel, Birkhäuser Okt 2012, 2012
ISBN 10: 3034894082
ISBN 13: 9783034894081
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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). 228 pp. Englisch. Seller Inventory # 9783034894081
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Markov Chains and Invariant Probabilities
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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). Seller Inventory # 9783034894081
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Markov Chains and Invariant Probabilities
Published by
Birkhäuser Basel, Birkhäuser Basel Okt 2012, 2012
ISBN 10: 3034894082
ISBN 13: 9783034894081
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Taschenbuch
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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).Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 228 pp. Englisch. Seller Inventory # 9783034894081
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Markov Chains and Invariant Probabilities (Paperback)
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Paperback. Condition: new. Paperback. 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). = {~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, . 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 ~. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783034894081
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Markov Chains and Invariant Probabilities (Progress in Mathematics)
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