Probability and Measure Theory,
Edition 2
By Robert B. Ash and Catherine A. Doleans-Dade

Publication Date: 06 Dec 1999
Description
Probability and Measure Theory, Second Edition, is a text for a graduate-level course in probability that includes essential background topics in analysis. It provides extensive coverage of conditional probability and expectation, strong laws of large numbers, martingale theory, the central limit theorem, ergodic theory, and Brownian motion.

Key Features

  • Clear, readable style
  • Solutions to many problems presented in text
  • Solutions manual for instructors
  • Material new to the second edition on ergodic theory, Brownian motion, and convergence theorems used in statistics
  • No knowledge of general topology required, just basic analysis and metric spaces
  • Efficient organization
About the author
By Robert B. Ash, University of Illinois, Urbana-Champaign, U.S.A.; and Catherine A. Doleans-Dade, University of Illinois, Urbana-Champaign, U.S.A.
Table of Contents
Summary of Notation
Fundamentals of Measure and Integration Theory.
Further Results in Measure and Integration Theory.
Introduction to Functional Analysis.
Basic Concepts of Probability.
Conditional Probability and Expectation.
Strong Laws of Large Numbers and Martingale Theory.
The Central Limit Theorem.
Ergodic Theory.
Brownian Motion and Stochastic Integrals.
Book details
ISBN: 9780120652020
Page Count: 528
Retail Price : £90.00
Ross: INTRODUCTION TO PROBABILITY MODELS, FIFTH EDITION (1993, ISBN: 0-12-598455-3)
Taylor/Karlin: AN INTRODUCTION TO STOCHASTIC MODELING, REVISED EDITION (1993, ISBN: 0-12-684885-8)
Chung: A COURSE IN PROBABILITY THEORY, SECOND EDITION (1974, ISBN: 0-12-174650-X)
Allen: PROBABILITY, STATISTICS, AND QUEING THEORY, SECOND EDITION (1990, ISBN: 0-12-051051-0)
Instructor Resources
Audience
Graduate students, faculty, and other professionals in mathematics, statistics, engineering, and economics; also, graduate students and professionals in physics and computer science