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More copies of this ISBN:This title in other formats:Other titles in the Diffusions, Markov Processes & Martingales series:Diffusions, Markov Processes & Martingales #01: Diffusions, Markov Processes, and Martingales: Volume 1, Foundationsby L C G Rogers
Synopses & ReviewsPublisher Comments:Now available in paperback, this celebrated book remains a key systematic guide to a large part of the modern theory of Probability. The authors not only present the subject of Brownian motion as a dry part of mathematical analysis, but convey its real meaning and fascination. The opening, heuristic chapter does just this, and it is followed by a comprehensive and self-contained account of the foundations of theory of stochastic processes. Chapter 3 is a lively presentation of the theory of Markov processes. Together with its companion volume, this book equips graduate students for research into a subject of great intrinsic interest and wide applications. Book News Annotation:This graduate level textbook deals with Brownian motion, the theory
of stochastic processes, and the theory of Markov processes. Topics
include Gaussian processes, continuous-parameter supermartingales,
probability measure on Lusin spaces, Feller-Dynkin processes,
additive functionals, and Ray processes. The second edition extends
the coverage of Brownian motion and stochastic processes.
Annotation c. Book News, Inc., Portland, OR (booknews.com) Synopsis:Now available in paperback for the first time; essential reading for all students of probability theory. Synopsis:Now available in paperback for the first time; essential reading for all students of probability theory. Table of ContentsSome frequently used notation; 1. Brownian motion; Part I. Introduction; 2. Basics about Brownian motion; 3. Brownian motion in higher dimensions; 4. Gaussian processes and Lévy processes; Part II. Some Classical Theory; 5. Basic measure theory; 6. Basic probability theory; 7. Stochastic processes; 8. Discrete-parameter martingale theory; 9. Continuous-parameter martingale theory; 10. Probability measure on Lusin spaces; Part III. Markov Processes: 11. Transition functions and resolvents; 12. Feller-Dynkin processes; 13. Additive functionals; 14. Approach to ray processes: the Martin boundary; 15. Ray processes; 16. Applications; References; Index.
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