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Item Details
Title: AN INTRODUCTION TO MARKOV PROCESSES
By: Daniel W. Stroock
Format: Paperback

List price: £44.99


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 3662517825
ISBN 13: 9783662517826
Publisher: SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG
Pub. date: 23 August, 2016
Edition: Softcover reprint of the original 2nd ed. 2014
Series: Graduate Texts in Mathematics 230
Pages: 203
Description: This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. Topics covered include: Doeblin's theory, general ergodic properties, and continuous time processes.
Synopsis: This book provides a rigorous but elementary introduction to the theory of Markov Processes on a countable state space. It should be accessible to students with a solid undergraduate background in mathematics, including students from engineering, economics, physics, and biology. Topics covered are: Doeblin's theory, general ergodic properties, and continuous time processes. Applications are dispersed throughout the book. In addition, a whole chapter is devoted to reversible processes and the use of their associated Dirichlet forms to estimate the rate of convergence to equilibrium. These results are then applied to the analysis of the Metropolis (a.k.a simulated annealing) algorithm.The corrected and enlarged 2nd edition contains a new chapter in which the author develops computational methods for Markov chains on a finite state space. Most intriguing is the section with a new technique for computing stationary measures, which is applied to derivations of Wilson's algorithm and Kirchoff's formula for spanning trees in a connected graph.
Illustrations: XVII, 203 p.
Publication: Germany
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Returns: Returnable
Some other items by this author:
A CONCISE INTRODUCTION TO ANALYSIS (PB)
A CONCISE INTRODUCTION TO INTEGRATION THEORY (HB)
A CONCISE INTRODUCTION TO THE THEORY OF INTEGRATION (HB)
A CONCISE INTRODUCTION TO THE THEORY OF INTEGRATION (HB)
AN INTRODUCTION TO MARKOV PROCESSES (HB)
AN INTRODUCTION TO MARKOV PROCESSES (PB)
AN INTRODUCTION TO THE ANALYSIS OF PATHS ON A RIEMANNIAN MANIFOLD (PB)
CONCISE INTRODUCTION TO THE THEORY OF INTEGRATION, A (HB)
ELEMENTS OF STOCHASTIC CALCULUS AND ANALYSIS (HB)
ESSENTIALS OF INTEGRATION THEORY FOR ANALYSIS
ESSENTIALS OF INTEGRATION THEORY FOR ANALYSIS (HB)
ESSENTIALS OF INTEGRATION THEORY FOR ANALYSIS (HB)
ESSENTIALS OF INTEGRATION THEORY FOR ANALYSIS (PB)
GAUSSIAN MEASURES IN FINITE AND INFINITE DIMENSIONS
LARGE DEVIATIONS (HB)
LECTURES ON STOCHASTIC ANALYSIS: DIFFUSION THEORY
LECTURES ON STOCHASTIC ANALYSIS: DIFFUSION THEORY (HB)
LECTURES ON STOCHASTIC ANALYSIS: DIFFUSION THEORY (PB)
MALLIAVIN CALCULUS AT SAINT-FLOUR (PB)
MARKOV PROCESSES FROM K. ITO'S PERSPECTIVE (AM-155)
MARKOV PROCESSES FROM K. ITO'S PERSPECTIVE (AM-155) (PB)
MARKOV PROCESSES FROM K. ITO'S PERSPECTIVE (HB)
MATHEMATICS OF PROBABILITY
MULTIDIMENSIONAL DIFFUSION PROCESSES (HB)
MULTIDIMENSIONAL DIFFUSION PROCESSES (HB)
MULTIDIMENSIONAL DIFFUSION PROCESSES (PB)
PARTIAL DIFFERENTIAL EQUATIONS FOR PROBABILISTS
PARTIAL DIFFERENTIAL EQUATIONS FOR PROBABILISTS
PARTIAL DIFFERENTIAL EQUATIONS FOR PROBABILISTS (HB)
PARTIAL DIFFERENTIAL EQUATIONS FOR PROBABILISTS (PB)
PROBABILITY THEORY
PROBABILITY THEORY (HB)
PROBABILITY THEORY (PB)
PROBABILITY THEORY, AN ANALYTIC VIEW (HB)
PROBABILITY THEORY, AN ANALYTIC VIEW (PB)
SELECTED PAPERS (HB)
THE LEGACY OF NORBERT WIENER (HB)

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