Markov processes, Gaussian processes, and local times /

Markov processes, Gaussian processes, and local times /

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Bibliographic Details
Author / Creator:	Marcus, Michael B.
Imprint:	New York : Cambridge University Press, 2006.
Description:	1 online resource (x, 620 pages).
Language:	English
Series:	Cambridge studies in advanced mathematics ; 100 Cambridge studies in advanced mathematics ; 100.
Subject:	Markov processes. Gaussian processes. Local times (Stochastic processes) Gaussian processes. Local times (Stochastic processes) Markov processes. Electronic books.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11812798

Hidden Bibliographic Details
Other authors / contributors:	Rosen, Jay, 1948-
ISBN:	9780511246968 051124696X 0511244819 9780511244810 0511245564 9780511245565 0521863007 9780521863001
Notes:	Includes bibliographical references (pages 603-610) and indexes. Print version record.
Summary:	Two foremost researchers present important advances in stochastic process theory by linking well understood (Gaussian) and less well understood (Markov) classes of processes. It builds to this material through 'mini-courses' on the relevant ingredients, which assume only measure-theoretic probability. This original, readable book is for researchers and advanced graduate students.
Other form:	Print version: Marcus, Michael B. Markov processes, Gaussian processes, and local times. New York : Cambridge University Press, 2006 9780521863001 0521863007
Standard no.:	9780521863001

Description
Summary:	Written by two foremost researchers in the field, this book studies the local times of Markov processes by employing isomorphism theorems that relate them to certain associated Gaussian processes. It builds to this material through self-contained but harmonized 'mini-courses' on the relevant ingredients, which assume only knowledge of measure-theoretic probability. The streamlined selection of topics creates an easy entrance for students and for experts in related fields. The book starts by developing the fundamentals of Markov process theory and then of Gaussian process theory, including sample path properties. It then proceeds to more advanced results, bringing the reader to the heart of contemporary research. It presents the remarkable isomorphism theorems of Dynkin and Eisenbaum then shows how they can be applied to obtain new properties of Markov processes by using well-established techniques in Gaussian process theory. This original, readable book will appeal to both researchers and advanced graduate students.
Physical Description:	1 online resource (x, 620 pages).
Bibliography:	Includes bibliographical references (pages 603-610) and indexes.
ISBN:	9780511246968 051124696X 0511244819 9780511244810 0511245564 9780511245565 0521863007 9780521863001