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Science/Engineering Stochastic Processes (Classics in Applied Mathematics)

Posted on 2010-03-16




Name:Science/Engineering Stochastic Processes (Classics in Applied Mathematics)
ASIN/ISBN:0898714419
Language:English
File size:260 Mb
ISBN: 0898714419
Publish Date: September 1, 1999
File Type: PDF (OCR)
Pages: 344 pages
File Size: 12964 KB
Other Info: Society for Industrial Mathematics
   Science/Engineering Stochastic Processes (Classics in Applied Mathematics)

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Stochastic Processes (Classics in Applied Mathematics): Emanuel Parzen

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.

Book Description

Ideal for courses 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.

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