Probability
Will be published approx. on 31. May 1992
Book
Paperback/Softback
434 pages
978-0-89871-296-4 (ISBN)
Description
Well known for the clear, inductive nature of its exposition, this reprint volume is an excellent introduction to mathematical probability theory. It may be used as a graduate-level text in one- or two-semester courses in probability for students who are familiar with basic measure theory, or as a supplement in courses in stochastic processes or mathematical statistics.
Designed around the needs of the student, this book achieves readability and clarity by giving the most important results in each area while not dwelling on any one subject. Each new idea or concept is introduced from an intuitive, common-sense point of view. Students are helped to understand why things work, instead of being given a dry theorem-proof regime.
Designed around the needs of the student, this book achieves readability and clarity by giving the most important results in each area while not dwelling on any one subject. Each new idea or concept is introduced from an intuitive, common-sense point of view. Students are helped to understand why things work, instead of being given a dry theorem-proof regime.
Reviews / Votes
'This excellent textbook by L. Breiman, which was used by many people to learn probability and which was out of print for some years, is again available as an unchanged republication. It gives an introduction to probability based on measure theory.' F. Hofbauer, Monatschefte fuer Mathematik 'A reprint of the 1986 Addison-Wesley text, long out of print (TR, October 1968). This is one of the true classics in the field of probability and its reappearance is welcome. At this price it belongs on the shelf of every student and professional in the area.' American Mathematical Monthly 'The style of writing is very informal and chatty. With a few exceptions this goes over quite well. Though one might reproach the author with an undue haste in keeping the reader's attention, and in skimming the cream of many subjects, the overall effect is good and may to some extent alleviate the discouragement of many non-specialists who want a reasonably modern account not overly encumbered with heavy analytic and set-theoretic preliminaries.' D. A. Darling, Mathematical Reviews 'This book is written on an advanced graduate level and addresses statisticians, engineers, and mathematicians who are interested in probability theory and measure and function theory.' Ion A. Craciun, RecenziiMore details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 234 mm
Width: 154 mm
Thickness: 27 mm
Weight
610 gr
ISBN-13
978-0-89871-296-4 (9780898712964)
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
Content
Chapter 1: Introduction
Chapter 2: Mathematical Framework
Chapter 3: Independence
Chapter 4: Conditional Probability and Conditional Expectation
Chapter 5: Martingales
Chapter 6: Stationary Processes and the Ergodic Theorem
Chapter 7: Markov Chains
Chapter 8: Convergence in Distribution and the Tools Thereof
Chapter 9: The One-Dimensional Central Limit Problem
Chapter 10: The Renewal Theorem and Local Limit Theorem
Chapter 11: Multidimensional Central Limit Theorem and Gaussian Processes
Chapter 12: Stochastic Processes and Brownian Motion
Chapter 13: Invariance Theorems
Chapter 14: Martingales and Processes with Stationary, Independent Increments
Chapter 15: Markov Processes, Introduction and Pure Jump Case
Chapter 16: Diffusions
Appendix: On Measure and Function Theory
Bibliography
Index.
Chapter 2: Mathematical Framework
Chapter 3: Independence
Chapter 4: Conditional Probability and Conditional Expectation
Chapter 5: Martingales
Chapter 6: Stationary Processes and the Ergodic Theorem
Chapter 7: Markov Chains
Chapter 8: Convergence in Distribution and the Tools Thereof
Chapter 9: The One-Dimensional Central Limit Problem
Chapter 10: The Renewal Theorem and Local Limit Theorem
Chapter 11: Multidimensional Central Limit Theorem and Gaussian Processes
Chapter 12: Stochastic Processes and Brownian Motion
Chapter 13: Invariance Theorems
Chapter 14: Martingales and Processes with Stationary, Independent Increments
Chapter 15: Markov Processes, Introduction and Pure Jump Case
Chapter 16: Diffusions
Appendix: On Measure and Function Theory
Bibliography
Index.