Probability Theory
An Analytic View
2nd Edition
Published on 31. December 2010
Book
Paperback/Softback
548 pages
978-0-521-13250-3 (ISBN)
Description
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.
Reviews / Votes
'... uniformly well written and well spiced with comments to aid the intuition, so the readership should include a wide range, both of students and of professional probabilists. ... We can expect it to take its place alongside the classics of probability theory.' Mathematical ReviewsMore details
Edition
2nd Revised edition
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Edition type
Revised edition
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises
Dimensions
Height: 254 mm
Width: 179 mm
Thickness: 27 mm
Weight
910 gr
ISBN-13
978-0-521-13250-3 (9780521132503)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Daniel W. Stroock
Probability Theory, An Analytic View
Book
11/2024
3rd Edition
Cambridge University Press
€64.00
Shipment within 15-20 days
Additional editions
E-Book
03/2011
2nd Edition
Cambridge University Press
€51.99
Available for download
Previous edition
Daniel W. Stroock
Probability Theory, an Analytic View
Book
01/2000
Cambridge University Press
€52.08
Article exhausted; check for reprint
Person
Dr Daniel W. Stroock is the Simons Professor of Mathematics Emeritus at the Massachusetts Institute of Technology. He has published numerous articles and is the author of six books, most recently Partial Differential Equations for Probabilists (2008).
Content
1. Sums of independent random variables; 2. The central limit theorem; 3. Infinitely divisible laws; 4. Levy processes; 5. Conditioning and martingales; 6. Some extensions and applications of martingale theory; 7. Continuous parameter martingales; 8. Gaussian measures on a Banach space; 9. Convergence of measures on a Polish space; 10. Wiener measure and partial differential equations; 11. Some classical potential theory.