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Markov chains

Author: J R Norris
Publisher: Cambridge, UK ; New York : Cambridge University Press, 1998.
Series: Cambridge series on statistical and probabilistic mathematics.
Edition/Format:   Print book : English : 1st pbk. edView all editions and formats
Summary:
Publisher Description (unedited publisher data) Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: J R Norris
ISBN: 0521481813 9780521481816 0521633966 9780521633963
OCLC Number: 35043455
Description: xvi, 237 pages : illustrations ; 26 cm.
Contents: 1. Discrete-time Markov chains. 1.1 Definition and basic properties. 1.2 Class structure. 1.3 Hitting times and absorption probabilities. 1.4 Strong Markov property. 1.5 Recurrence and transience. 1.6 Recurrence and transience of random walks. 1.7 Invariant distributions. 1.8 Convergence to equilibrium. 1.9 Time reversal. 1.10 Ergodic theorem. 1.11 Appendix: Recurrence relations. 1.12 Appendix: Asymptotics for n! --
2. Continuous-time Markov chains I. 2.1 Q-matrices and their exponentials. 2.2 Continuous-time random processes. 2.3 Some properties of the exponential distribution. 2.4 Poisson processes. 2.5 Birth processes. 2.6 Jump chain and holding times. 2.7 Explosion. 2.8 Forward and backward equations. 2.9 Non-minimal chains. 2.10 Appendix: Matrix exponentials --
3. Continuous-time Markov chains II. 3.1 Basic properties. 3.2 Class structure. 3.3 Hitting times and absorption probabilities. 3.4 Recurrence and transience. 3.5 Invariant distributions.
Series Title: Cambridge series on statistical and probabilistic mathematics.
Responsibility: J.R. Norris.
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A textbook for students with some background in probability that develops quickly a rigorous theory of Markov chains and shows how actually to apply it, e.g. to simulation, economics, optimal  Read more...

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'This is an admirable book, treating the topic with mathematical rigour and clarity, mixed with helpful informality; and emphasising numerous applications to a wide range of subjects.' D. V. Lindley, Read more...

 
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