Markov Chains and Stochastic Stability
Author:   Sean P. Meyn ,  Richard L. Tweedie
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Edition. ed.
ISBN:  

9783540198321


Pages:   566
Publication Date:   June 1993
Format:   Hardback
Availability:   Out of stock   Availability explained
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Markov Chains and Stochastic Stability


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Overview

The area of Markov chain theory and application has matured over the past 20 years. This publication deals with the action of Markov chains on general state spaces. It discusses the theories and the use to be gained, concentrating on the areas of engineering, operations research and control theory. Throughout, the theme of stochastic stability and the search for practical methods of verifying such stability, provide a new and powerful technique which not only affects applications, but also the development of the theory itself. The impact of the theory on specific models is discussed in detail.

Full Product Details

Author:   Sean P. Meyn ,  Richard L. Tweedie
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Edition. ed.
Weight:   0.975kg
ISBN:  

9783540198321


ISBN 10:   3540198326
Pages:   566
Publication Date:   June 1993
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Contents: Communication and Regeneration: Heuristics.- Markov Models.- Transition Probabilities.- Irreducibility.- Pseudo-atoms.- Topology and Continuity.- Nonlinear State Space Model.- Stability Structures: Transience and Recurrence.- Harris and Topological Recurrence.- The Existence of +.- Drift and Regularity.- Invariance and Tightness. Convergence: Ergodicity.- f-Ergodicity and f-Regularity.- Geometric Ergodicity.- V-Uniform Ergodicity.- Sample Paths and Limit Theorems.- Positivity.- Generalised Classification Criteria. Appendices: Mud Maps.- Testing for Stability.- Glossary of Model Assumptions.- Mathematical Background.

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