| Hardcover ISBN: | 978-0-8218-4949-1 |
| Product Code: | GSM/113 |
| List Price: | $62.00 |
| MAA Member Price: | $55.80 |
| AMS Member Price: | $49.60 |
| Electronic ISBN: | 978-1-4704-1175-6 |
| Product Code: | GSM/113.E |
| List Price: | $58.00 |
| MAA Member Price: | $52.20 |
| AMS Member Price: | $46.40 |
-
Book DetailsGraduate Studies in MathematicsVolume: 113; 2010; 271 ppMSC: Primary 60; Secondary 35;
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.ReadershipGraduate students and research mathematicians interested in probability.
-
Table of Contents
-
Chapters
-
Chapter 1. One-dimensional Brownian motion
-
Chapter 2. Continuous time Markov chains
-
Chapter 3. Feller processes
-
Chapter 4. Interacting particle systems
-
Chapter 5. Stochastic integration
-
Chapter 6. Multi-dimensional Brownian motion and the Dirichlet problem
-
Appendix
-
-
Additional Material
-
RequestsReview Copy – for reviewers who would like to review an AMS bookDesk Copy – for instructors who have adopted an AMS textbook for a courseExamination Copy – for faculty considering an AMS textbook for a coursePermission – for use of book, eBook, or Journal contentAccessibility – to request an alternate format of an AMS title
- Book Details
- Table of Contents
- Additional Material
- Requests
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.
Graduate students and research mathematicians interested in probability.
-
Chapters
-
Chapter 1. One-dimensional Brownian motion
-
Chapter 2. Continuous time Markov chains
-
Chapter 3. Feller processes
-
Chapter 4. Interacting particle systems
-
Chapter 5. Stochastic integration
-
Chapter 6. Multi-dimensional Brownian motion and the Dirichlet problem
-
Appendix
