Continuous Time Markov Processes :An Introduction ( Graduate Studies in Mathematics )

Publication subTitle :An Introduction

Publication series :Graduate Studies in Mathematics

Author: Thomas M. Liggett  

Publisher: American Mathematical Society‎

Publication year: 2010

E-ISBN: 9781470411756

P-ISBN(Paperback): 9780821849491

Subject: O211.62 Markov process

Keyword: Probability and Statistics

Language: ENG

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Continuous Time Markov Processes

Description

Markov processes are among the most important stochastic processes for both theory and applications. This book develops the general theory of these processes and applies this theory to various special examples. The initial chapter is devoted to the most important classical example—one-dimensional Brownian motion. This, together with a chapter on continuous time Markov chains, provides the motivation for the general setup based on semigroups and generators. Chapters on stochastic calculus and probabilistic potential theory give an introduction to some of the key areas of application of Brownian motion and its relatives. A chapter on interacting particle systems treats a more recently developed class of Markov processes that have as their origin problems in physics and biology. This is a textbook for a graduate course that can follow one that covers basic probabilistic limit theorems and discrete time processes.

Chapter

Title page

Contents

Preface

One-dimensional Brownian motion

Continuous time Markov chains

Feller processes

Interacting particle systems

Stochastic integration

Multidimensional Brownian motion and the Dirichlet problem

Appendix

Bibliography

Index

Back Cover

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