Probability Theory

A second edition of Daniel W. Stroock's classic probability theory textbook suitable for first-year graduate students with a good grasp of introductory, undergraduate probability.

Informationen zum Autor 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). Klappentext A second edition of Daniel W. Stroock's classic probability theory textbook suitable for first-year graduate students with a good grasp of introductory! undergraduate probability. Zusammenfassung This second edition of Daniel W. Stroock's classic probability theory textbook is suitable for first-year graduate students with a good grasp of introductory! undergraduate probability. It includes more than 750 exercises and revised material on the treatment of Levy processes and a detailed account of Gaussian measures on a Banach space. Inhaltsverzeichnis 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.

Klappentext
A second edition of Daniel W. Stroock's classic probability theory textbook suitable for first-year graduate students with a good grasp of introductory, undergraduate probability.


Zusammenfassung
This second edition of Daniel W. Stroock's classic probability theory textbook is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability. It includes more than 750 exercises and revised material on the treatment of Levy processes and a detailed account of Gaussian measures on a Banach space.

Inhalt
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.

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