A User's Guide to Measure Theoretic Probability

This book grew from a one-semester course offered for many years to a mixed audience of graduate and undergraduate students who have not had the luxury of taking a course in measure theory. The core of the book covers the basic topics of independence, conditioning, martingales, convergence in distribution, and Fourier transforms. In addition there are numerous sections treating topics traditionally thought of as more advanced, such as coupling and the KMT strong approximation, option pricing via the equivalent martingale measure, and the isoperimetric inequality for Gaussian processes. The book is not just a presentation of mathematical theory, but is also a discussion of why that theory takes its current form. It will be a secure starting point for anyone who needs to invoke rigorous probabilistic arguments and understand what they mean.

Author: David Pollard
Publisher: Cambridge University Press
Published: 12/17/2001
Pages: 366
Binding Type: Hardcover
Weight: 1.87lbs
Size: 10.00h x 7.01w x 0.81d
ISBN: 9780521802420

Review Citation(s):
Choice 11/01/2002 pg. 506

This title is not returnable