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Probability: Theory and Examples
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Probability: Theory and Examples Hardcover - 2019

by Rick Durrett


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This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of It's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new edition re-instates discussion about the central limit theorem for martingales and stationary sequences.

Details

  • Title Probability: Theory and Examples
  • Author Rick Durrett
  • Binding Hardcover
  • Pages 430
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Date 2019-04-18
  • ISBN 9781108473682 / 1108473687
  • Weight 2 lbs (0.91 kg)
  • Dimensions 10 x 9.5 x 1.1 in (25.40 x 24.13 x 2.79 cm)
  • Library of Congress subjects Probabilities
  • Library of Congress Catalog Number 2018047195
  • Dewey Decimal Code 519.2
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Probability: Theory and Examples
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Probability: Theory and Examples
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ISBN: 9781108473682
Cambridge University Press, 01 January 2019
Hardback, 430 pages
This lively introduction to measure-theoretic probability theory covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. Concentrating on results that are the most useful for applications, this comprehensive treatment is a rigorous graduate text and reference. Operating under the philosophy that the best way to learn probability is to see it in action, the book contains extended examples that apply the theory to concrete applications. This fifth edition contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), an advanced topic that is finding new applications. Setting the foundation for this expansion, Chapter 7 now features a proof of It's formula. Key exercises that previously were simply proofs left to the reader have been directly inserted into the text as lemmas. The new… Read More
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