"This text provides a rigorous, yet entertaining, introduction to modern probability theory and the analytic ideas and tools on which it relies. The third edition includes a new treatment of the Gaussian isoperimetric inequality and numerous improvements and clarifications. With more than 750 exercises, it is ideal for first-year graduate students"--
"This text provides a rigorous, yet entertaining, introduction to modern probability theory and the analytic ideas and tools on which it relies. The third edition includes a new treatment of the Gaussian isoperimetric inequality and numerous improvements and clarifications. With more than 750 exercises, it is ideal for first-year graduate students"--Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Daniel W. Stroock is Simons Professor Emeritus of Mathematics at the Massachusetts Institute of Technology. He has published numerous articles and books, most recently 'Elements of Stochastic Calculus and Analysis' (2018) and 'Gaussian Measures in Finite and Infinite Dimensions' (2023).
Inhaltsangabe
Notation 1. Sums of independent random variables 2. The central limit theorem 3. Infinitely divisible laws 4. Lévy 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 References Index.
Notation 1. Sums of independent random variables 2. The central limit theorem 3. Infinitely divisible laws 4. Lévy 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 References Index.
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