
Probability and Measure Theory
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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
Readership
Graduate students, faculty, and other professionals in mathematics, statistics, engineering, and economics; also, graduate students and professionals in physics and computer science
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.
Product details
- No. of pages: 516
- Language: English
- Copyright: © Academic Press 1999
- Published: November 15, 1999
- Imprint: Academic Press
- Hardcover ISBN: 9780120652020
About the Authors
Robert Ash
Robert B. Ash as written about, taught, or studied virtually every area of mathematics. His books include Information Theory, Topics in Stochastic Processes, The Calculus Tutoring Book, Introduction to Discrete Mathematics, and A Primer of Mathematics.
Affiliations and Expertise
University of Illinois, Urbana-Champaign, U.S.A.
Catherine Doleans-Dade
Affiliations and Expertise
University of Illinois, Urbana-Champaign, U.S.A.
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