Markov Chains: With Stationary Transition Probabilities

Author:   Kai Lai Chung
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Softcover reprint of the original 2nd ed. 1967
Volume:   104
ISBN:  

9783642620171


Pages:   301
Publication Date:   17 July 2012
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Markov Chains: With Stationary Transition Probabilities


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Overview

From the reviews: J. Neveu, 1962 in Zentralblatt fur Mathematik, 92.Band Heft 2, p. 343: ""Ce livre ecrit par l'un des plus eminents specialistes en la matiere, est un expose tres detaille de la theorie des processus de Markov definis sur un espace denombrable d'etats et homogenes dans le temps (chaines stationnaires de Markov)."" N.Jain, 2008 in Selected Works of Kai Lai Chung, edited by Farid AitSahlia (University of Florida, USA), Elton Hsu (Northwestern University, USA), & Ruth Williams (University of California-San Diego, USA), Chapter 1, p. 15: ""This monograph deals with countable state Markov chains in both discrete time (Part I) and continuous time (Part II). [...] Much of Kai Lai's fundamental work in the field is included in this monograph. Here, for the first time, Kai Lai gave a systematic exposition of the subject which includes classification of states, ratio ergodic theorems, and limit theorems for functionals of the chain.""

Full Product Details

Author:   Kai Lai Chung
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 2nd ed. 1967
Volume:   104
Dimensions:   Width: 15.50cm , Height: 1.60cm , Length: 23.50cm
Weight:   0.486kg
ISBN:  

9783642620171


ISBN 10:   3642620175
Pages:   301
Publication Date:   17 July 2012
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

I. Discrete Parameter.- § 1. Fundamental definitions.- § 2. Transition probabilities.- § 3. Classification of states.- § 4. Recurrence.- § 5. Criteria and examples.- § 6. The main limit theorem.- § 7. Various complements.- § 8. Repetitive pattern and renewal process.- § 9. Taboo probabilities.- § 10. The generating function.- § 11. The moments of first entrance time distributions.- § 12. A random walk example.- § 13. System theorems.- § 14. Functionals and associated random variables.- § 15. Ergodic theorems.- § 16. Further limit theorems.- § 17. Almost closed and sojourn sets.- II. Continuous Parameter.- § 1. Transition matrix: basic properties.- § 2. Standard transition matrix.- § 3. Differentiability.- § 4. Definitions and measure-theoretic foundations.- § 5. The sets of constancy.- § 6. Continuity properties of sample functions.- § 7. Further specifications of the process.- § 8. Optional random variable.- § 9. Strong Markov property.- § 10. Classification of states.- § 11. Taboo probability functions.- § 12. Last exit time.- § 13. Ratio limit theorems; discrete approximations.- § 14. Functionals.- § 15. Post-exit process.- § 16. Imbedded renewal process.- § 17. The two systems of differential equations.- § 18. The minimal solution.- § 19. The first infinity.- § 20. Examples.

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