
Stochastic Processes
Emanuel Parzen(Author)
Society for Industrial & Applied Mathematics,U.S. (Publisher)
Will be published approx. on 30. June 1999
Book
Paperback/Softback
343 pages
978-0-89871-441-8 (ISBN)
Description
This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.
Stochastic Processes is ideal for a course aiming to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models. It introduces the methods of probability model building and provides the reader with mathematically sound techniques as well as the ability to further study the theory of stochastic processes.
Originally published in 1962, this was the first comprehensive survey of stochastic processes requiring only a minimal background in introductory probability theory and mathematical analysis. Stochastic Processes continues to be unique, with many topics and examples still not discussed in other textbooks. As new fields of applications (such as finance and DNA analysis) become important, researchers will continue to find the fundamental and accessible topics explained in this book essential background for their research.
Stochastic Processes is ideal for a course aiming to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models. It introduces the methods of probability model building and provides the reader with mathematically sound techniques as well as the ability to further study the theory of stochastic processes.
Originally published in 1962, this was the first comprehensive survey of stochastic processes requiring only a minimal background in introductory probability theory and mathematical analysis. Stochastic Processes continues to be unique, with many topics and examples still not discussed in other textbooks. As new fields of applications (such as finance and DNA analysis) become important, researchers will continue to find the fundamental and accessible topics explained in this book essential background for their research.
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
College/higher education
Product notice
Paperback (trade)
Dimensions
Height: 282 mm
Width: 150 mm
Thickness: 19 mm
Weight
484 gr
ISBN-13
978-0-89871-441-8 (9780898714418)
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
Preface to the Classics Edition
Preface
Role of the Theory of Stochastic Processes
Chapter 1: Random Variables and Stochastic Processes
Chapter 2: Conditional Probability and Conditional Expectation
Chapter 3: Normal Processes and Covariance Stationary Processes
Chapter 4: Counting Processes and Poisson Processes
Chapter 5: Renewal Counting Processes
Chapter 6: Markov Chains: Discrete Parameter
Chapter 7: Markov Chains: Continuous Parameter
References
Author Index
Subject Index.
Preface
Role of the Theory of Stochastic Processes
Chapter 1: Random Variables and Stochastic Processes
Chapter 2: Conditional Probability and Conditional Expectation
Chapter 3: Normal Processes and Covariance Stationary Processes
Chapter 4: Counting Processes and Poisson Processes
Chapter 5: Renewal Counting Processes
Chapter 6: Markov Chains: Discrete Parameter
Chapter 7: Markov Chains: Continuous Parameter
References
Author Index
Subject Index.