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Introduction to Markov Chains With Special Emphasis on Rapid Mixing

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Published by Friedrick Vieweg & Son .
Written in English

Subjects:

  • Mathematics,
  • Science/Mathematics,
  • Advanced

Book details:

The Physical Object
FormatPaperback
ID Numbers
Open LibraryOL9053120M
ISBN 103528069864
ISBN 109783528069865

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Get this from a library! Introduction to Markov chains: with special emphasis on rapid mixing. [Ehrhard Behrends] -- "Readership: graduate students and mathematicians. The book is self-contained, emphasis is laid on an extensive motivation of the ideas rather than . the methods treated in this book can be applied. Besides the investigation of general chains the book contains chapters which are concerned with eigenvalue techniques, conductance, stopping times, the strong Markov property, couplings, strong uniform times, Markov chains on . times, Markov chains on arbitrary finite groups (including a crash-course in harmonic analysis), random generation and counting, Markov random fields, Gibbs fields, the Metropolis sampler, and simulated annealing. Readers are invited to solve as many as possible of the exercises. The book is self-contained, emphasis is laid on an. Get this from a library! Introduction to Markov chains: with special emphasis on rapid mixing. [Ehrhard Behrends].

concerned with rapid mixing. Later I continued to discuss these problems with specialists from various fields, these efforts led to a course on "Rapidly mixing Markov chains" given in the winter term /98 at Free University of Berlin. It is a pleasure to acknowledge the help of . the mixing time grows as the size of the state space increases. The modern theory of Markov chain mixing is the result of the convergence, in the ’s and ’s, of several threads. (We mention only a few names here; see the chapter Notes for references.) For statistical physicists Markov chains become useful in Monte Carlo simu-. Book Reviewers; Instructors; Journalists; Librarians (Springer Nature) Introduction to Markov Chains With Special Emphasis on Rapid Mixing. Series: Advanced Lectures in Mathematics. Behrends, Ehrhard An Introduction. Reihe: Advanced Lectures in Mathematics, Band. Dimca. ample of a Markov chain on a countably infinite state space, but first we want to discuss what kind of restrictions are put on a model by assuming that it is a Markov chain. Within the class of stochastic processes one could say that Markov chains are characterised by .

Several other recent books treat Markov chain mixing. Our account is more comprehensive than those of Ha¨ggstr¨om (), Jerrum (), or Montenegro and Tetali (), yet not as exhaustive as Aldous and Fill (). Norris () gives an introduction to Markov chains and their applications, but does not focus on mix-ing. Markov Chains and Mixing Times David A. Levin Yuval Peres Elizabeth L. Wilmer Chapter 1. Introduction to Finite Markov Chains 3 Finite Markov Chains 3 Random Mapping Representation 6 Irreducibility and Aperiodicity 8 Random Walks on Graphs 9 this book there. Overview. Markov Chains with Special Emphasis on Rapid Mixing. Ehrhard Behrends Introduction to Markov Chains ~ Advanced Lectures Introduction to Markov Chains with Special Emphasis on Rapid Mixing IJ vleweg. The book is written far readers who have never met Markov chains before, but have. Markov Chains: An Introduction/Review — MASCOS Workshop on Markov Chains, April – p. Classification of states We call a state i recurrent or transient according as P(Xn = i for infinitely many n) is equal to one or zero. A recurrent state is a state to which the process.