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Field name	Details
Dewey Class	519.233
Title	An Introduction to Markov Processes ([Ebook]) / by Daniel W. Stroock.
Author	Stroock, Daniel W.
Other name(s)	SpringerLink (Online service)
Edition statement	2nd ed. 2014.
Publication	Berlin, Heidelberg Springer 2014.
Physical Details	XVII, 203 pages : online resource.
ISBN	9783642405235
Summary Note	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.:
Contents note	Preface -- Random Walks, a Good Place to Begin -- Doeblin's Theory for Markov Chains -- Stationary Probabilities -- More about the Ergodic Theory of Markov Chains -- Markov Processes in Continuous Time -- Reversible Markov Processes -- A minimal Introduction to Measure Theory -- Notation -- References -- Index.
System details note	Online access to this digital book is restricted to subscription institutions and access ia available through IP address (only for SISSA internal users)
Internet Site	http://dx.doi.org/10.1007/978-3-642-40523-5
Links to Related Works	Subject References: Differentiable dynamical systems . Distribution (Probability theory) . Dynamical systems and ergodic theory . Mathematics . Probability theory and stochastic processes . Authors: Stroock, Daniel W. . Corporate Authors: SpringerLink (Online service) . Series: Graduate texts in mathematics . GTM . Classification: 519.233 . 519.233 (DDC 22) .

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An Introduction to Markov Processes

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