Continuous time Markov processes an introduction
Liggett, Thomas M
Continuous time Markov processes an introduction Thomas M. Liggett - Providence, R.I American Mathematical Society c2010 - xii, 271 p 27 cm - Graduate studies in mathematics v. 113 . - Graduate studies in mathematics .
Contine bibliogr. si index
One-dimensional Brownian motion -- Continuous time Markov chains -- Feller processes -- Interacting particle systems -- Stochastic integration -- Multi-dimensional Brownian motion and the Dirichlet problem
"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."--Publisher's description
9780821849491 (Cloth) 0821849492 (Cloth)
2009045839
Markov processes
Stochastic integrals
519.2/33
Continuous time Markov processes an introduction Thomas M. Liggett - Providence, R.I American Mathematical Society c2010 - xii, 271 p 27 cm - Graduate studies in mathematics v. 113 . - Graduate studies in mathematics .
Contine bibliogr. si index
One-dimensional Brownian motion -- Continuous time Markov chains -- Feller processes -- Interacting particle systems -- Stochastic integration -- Multi-dimensional Brownian motion and the Dirichlet problem
"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."--Publisher's description
9780821849491 (Cloth) 0821849492 (Cloth)
2009045839
Markov processes
Stochastic integrals
519.2/33