An Introduction to Markov Processes

Released on by Daniel W. Stroock
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  • An Introduction to Markov Processes Book Detail

  • Author : Daniel W. Stroock
  • Release Date : 2013-10-28
  • Publisher : Springer Science & Business Media
  • Genre : Mathematics
  • Pages : 213
  • ISBN 13 : 3642405231
  • File Size : 63,63 MB
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An Introduction to Markov Processes by Daniel W. Stroock PDF Summary

Book Description: 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.

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An Introduction to Markov Processes

An Introduction to Markov Processes

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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

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Markov process theory provides a mathematical framework for analyzing the elements of randomness that are involved in most real-world dynamical processes. This

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Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model

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The modem theory of Markov processes has its origins in the studies of A. A. MARKOV (1906-1907) on sequences of experiments "connected in a chain" and in the at