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Continuous Time Markov Processes: An Introduction
 
Thomas M. Liggett University of California, Los Angeles, Los Angeles, CA
Continuous Time Markov Processes
Hardcover ISBN:  978-0-8218-4949-1
Product Code:  GSM/113
List Price: $99.00
MAA Member Price: $89.10
AMS Member Price: $79.20
eBook ISBN:  978-1-4704-1175-6
Product Code:  GSM/113.E
List Price: $85.00
MAA Member Price: $76.50
AMS Member Price: $68.00
Hardcover ISBN:  978-0-8218-4949-1
eBook: ISBN:  978-1-4704-1175-6
Product Code:  GSM/113.B
List Price: $184.00 $141.50
MAA Member Price: $165.60 $127.35
AMS Member Price: $147.20 $113.20
Continuous Time Markov Processes
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Continuous Time Markov Processes: An Introduction
Thomas M. Liggett University of California, Los Angeles, Los Angeles, CA
Hardcover ISBN:  978-0-8218-4949-1
Product Code:  GSM/113
List Price: $99.00
MAA Member Price: $89.10
AMS Member Price: $79.20
eBook ISBN:  978-1-4704-1175-6
Product Code:  GSM/113.E
List Price: $85.00
MAA Member Price: $76.50
AMS Member Price: $68.00
Hardcover ISBN:  978-0-8218-4949-1
eBook ISBN:  978-1-4704-1175-6
Product Code:  GSM/113.B
List Price: $184.00 $141.50
MAA Member Price: $165.60 $127.35
AMS Member Price: $147.20 $113.20
  • Book Details
     
     
    Graduate Studies in Mathematics
    Volume: 1132010; 271 pp
    MSC: 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.

    Readership

    Graduate 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
  • Requests
     
     
    Review Copy – for publishers of book reviews
    Desk Copy – for instructors who have adopted an AMS textbook for a course
    Examination Copy – for faculty considering an AMS textbook for a course
    Permission – for use of book, eBook, or Journal content
    Accessibility – to request an alternate format of an AMS title
Volume: 1132010; 271 pp
MSC: 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.

Readership

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
Review Copy – for publishers of book reviews
Desk Copy – for instructors who have adopted an AMS textbook for a course
Examination Copy – for faculty considering an AMS textbook for a course
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
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