Markov Chains and Invariant Probabilities

Onésimo Hernández-Lerma (1) , Jean-Bernard Lasserre (2)

1 Departamento de Matemáticas del Cinvestav-IPN
2 LAAS-MAC - Équipe Méthodes et Algorithmes en Commande

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.

Domaines: Optimisation et contrôle [math.OC]

Onésimo Hernández-Lerma, Jean-Bernard Lasserre. Markov Chains and Invariant Probabilities. Birkhäuser Basel, 2003, 978-3-0348-9408-1. ⟨10.1007/978-3-0348-8024-4⟩. ⟨hal-02095863⟩