Probability theory [electronic resource] : an analytic view / Daniel W. Stroock.

"This second edition of Daniel W. Stroock's text is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability theory and a sound grounding in analysis. It is intended to provide readers with an introduction to probability theory and the analytic ideas and...

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Bibliographic Details
Main Author: Stroock, Daniel W.
Language:English
Published: Cambridge ; New York : Cambridge University Press, 2011.
Edition:2nd ed.
Subjects:
Online Access:
Variant Title:
Probability Theory: An Analytic View
Format: Electronic eBook

MARC

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100 1 |a Stroock, Daniel W. 
245 1 0 |a Probability theory  |h [electronic resource] :  |b an analytic view /  |c Daniel W. Stroock. 
246 2 |a Probability Theory: An Analytic View 
250 |a 2nd ed. 
260 |a Cambridge ;  |a New York :  |b Cambridge University Press,  |c 2011. 
504 |a Includes bibliographical references and index. 
504 |a Includes bibliographical references and index. 
520 |a "This second edition of Daniel W. Stroock's text is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability theory and a sound grounding in analysis. It is intended to provide readers with an introduction to probability theory and the analytic ideas and tools on which the modern theory relies. It includes more than 750 exercises. Much of the content has undergone significant revision. In particular, the treatment of Levy processes has been rewritten, and a detailed account of Gaussian measures on a Banach space is given. The first part of the book deals with independent random variables, Central Limit phenomena, and the construction of Levy processes, including Brownian motion. Conditioning is developed and applied to discrete parameter martingales in Chapter 5, Chapter 6 contains the ergodic theorem and Burkholder's inequality, and continuous parameter martingales are discussed in Chapter 7. Chapter 8 is devoted to Gaussian measures on a Banach space, where they are treated from the abstract Wiener space perspective. The abstract theory of weak convergence is developed in Chapter 9, which ends with a proof of Donsker's Invariance Principle. The concluding two chapters contain applications of Brownian motion to the analysis of partial differential equations and potential theory"--  |c Provided by publisher. 
650 0 |a Probabilities. 
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773 0 |t eBook Academic Collection (EBSCOhost) – North America   |d EBSCO 
776 1 |t Probability theory  |w (DLC)2010027652 
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856 4 0 |y Access Content Online(from eBook Academic Collection (EBSCOhost) – North America)  |u https://ezproxy.msu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=e000xna&AN=357430  |z eBook Academic Collection (EBSCOhost) – North America: 2011