Probability : Theory and Examples Hardback
by Rick (Duke University, North Carolina) Durrett
Part of the Cambridge Series in Statistical and Probabilistic Mathematics series
Hardback
Description
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 Ito'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.
Information
-
Out of stock
- Format:Hardback
- Pages:430 pages, Worked examples or Exercises; 20 Line drawings, black and white
- Publisher:Cambridge University Press
- Publication Date:18/04/2019
- Category:
- ISBN:9781108473682
Information
-
Out of stock
- Format:Hardback
- Pages:430 pages, Worked examples or Exercises; 20 Line drawings, black and white
- Publisher:Cambridge University Press
- Publication Date:18/04/2019
- Category:
- ISBN:9781108473682
