Probability and Measure Theory
2nd Edition
Published on 8. December 1999
Book
Hardback
528 pages
978-0-12-065202-0 (ISBN)
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.
Reviews / Votes
"There are numerous probability texts on the market, which makes choosing one difficult. If you are a financial professional who knows basic probability theory, but wants to take the next step in sophistication, this is the essential text. It introduces basic measure theory and functional analysis, and then delves into probability. The writing is clear and highly accessible. The choice of topics is perfect for financial engineers or financial risk managers: martingales, the inversion theorem, the central limit theorem, Brownian motion and stochastic integrals. I can't praise this book enough. It is exceptional!" --http://www.contingencyanalysis.comMore details
Edition
2nd edition
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Graduate students, faculty, and other professionals in mathematics, statistics, engineering, and economics; graduate students and professionals in physics and computer science.
Edition type
New edition
Product notice
Laminated cover
Dimensions
Height: 235 mm
Width: 159 mm
Thickness: 42 mm
Weight
947 gr
ISBN-13
978-0-12-065202-0 (9780120652020)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
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.
Content
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
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