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Markov Chains and Invariant Probabilities

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 vario...

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Bibliographic Details
Main Authors: Hernández-Lerma, Onésimo, Lasserre, Jean B. (Author)
Format: eBook
Language:English
Published: Basel Birkhäuser 2003, 2003
Edition:1st ed. 2003
Series:Progress in Mathematics
Subjects:
Operations Research, Management Science
Operations Research
Management Science
Probability Theory
Mathematical Physics
Mathematical Methods In Physics
Probabilities
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 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

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