Probability - Theory and Examples

A well-written and lively introduction to measure theoretic probability for graduate students and researchers.

List of contents

1. Measure theory; 2. Laws of large numbers; 3. Central limit theorems; 4. Martingales; 5. Markov chains; 6. Ergodic theorems; 7. Brownian motion; 8. Applications to random walk; 9. Multidimensional Brownian motion; Appendix. Measure theory details.

About the author

Rick Durrett is a James B. Duke professor in the mathematics department of Duke University, North Carolina. He received his Ph.D. in Operations Research from Stanford University in 1976. After nine years at University of California, Los Angeles and twenty-five at Cornell University, he moved to Duke University in 2010. He is the author of 8 books and more than 220 journal articles on a wide variety of topics, and has supervised more than 45 Ph.D. students. He is a member of National Academy of Science, American Academy of Arts and Sciences, and a fellow of the Institute of Mathematical Statistics, and of the American Mathematical Society.

Summary

The new edition of this lively but rigorous introduction to measure theoretic probability theory, designed for use in a graduate course, contains a new chapter on multidimensional Brownian motion and its relationship to partial differential equations (PDEs), a topic that is finding new applications. Some 200 examples and 450 exercises help readers build practical intuition.

Product details

• Authors: Rick Durrett, Rick (Duke University Durrett, Durrett Rick
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 30.04.2019
• EAN: 9781108473682
• ISBN: 978-1-108-47368-2
• No. of pages: 430
• Series: Cambridge Series in Statistica; Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge Series in Statistica; Cambridge Statistical and Prob
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / General, Probability & statistics, Probability and statistics