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Markov Processes, Gaussian Processes...

Ebooks Corporation.

Markov Processes, Gaussian Processes, and Local Times.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Markov Processes, Gaussian Processes, and Local Times.
作者:	Marcus, Michael B.
其他作者:	Rosen, Jay.
出版者:	Leiden :Cambridge University Press,2006.
面頁冊數:	632 p.
標題:	Markov processes.
電子資源:	Click here to view book
ISBN:	9780511617997 (electronic bk.)

Markov Processes, Gaussian Processes, and Local Times.
Marcus, Michael B.

Markov Processes, Gaussian Processes, and Local Times.[electronic resource]. - Leiden :Cambridge University Press,2006. - 632 p.

Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; 1 Introduction; 2 Brownian motion and Ray��night Theorems; 3 Markov processes and local times; 4 Constructing Markov processes; 5 Basic properties of Gaussian processes; 6 Continuity and boundedness of Gaussian processes; 7 Moduli of continuity for Gaussian processes; 8 Isomorphism Theorems; 9 Sample path properties of local times; 10 p-variation of Gaussian processes and local times; 11 Most visited sites of symmetric stable processes; 12 Local times of diffusions; Chapter 13 Associated Gaussian processes

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.

Electronic reproduction.

Available via World Wide Web.

Mode of access: World Wide Web.

ISBN: 9780511617997 (electronic bk.)Subjects--Topical Terms:

181910
Markov processes.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QA274.7 .M35 2006eb

Dewey Class. No.: 519.233

Markov Processes, Gaussian Processes, and Local Times.
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505 0 $a Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; 1 Introduction; 2 Brownian motion and Ray��night Theorems; 3 Markov processes and local times; 4 Constructing Markov processes; 5 Basic properties of Gaussian processes; 6 Continuity and boundedness of Gaussian processes; 7 Moduli of continuity for Gaussian processes; 8 Isomorphism Theorems; 9 Sample path properties of local times; 10 p-variation of Gaussian processes and local times; 11 Most visited sites of symmetric stable processes; 12 Local times of diffusions; Chapter 13 Associated Gaussian processes
505 8 $a Chapter 14 AppendixReferences; Index of notation; Author index; Subject index
520 $a 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.
533 $a Electronic reproduction. $n Available via World Wide Web.
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