Probability
eBook - PDF

Probability

Theory and Examples

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Probability

Theory and Examples

About this book

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 Itô'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.

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Yes, you can access Probability by Rick Durrett in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half-title
  3. Series information
  4. Title page
  5. Copyright information
  6. Contents
  7. Preface
  8. 1 Measure Theory
  9. 2 Laws of Large Numbers
  10. 3 Central Limit Theorems
  11. 4 Martingales
  12. 5 Markov Chains
  13. 6 Ergodic Theorems
  14. 7 Brownian Motion
  15. 8 Applications to Random Walk
  16. 9 Multidimensional Brownian Motion
  17. Appendix A Measure Theory Details
  18. References
  19. Index