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9780898714418 Academic Inspection Copy

Stochastic Processes

  • ISBN-13: 9780898714418
  • Publisher: SIAM - SOCIETY FOR INDUSTRIAL AND APPLIED
    Imprint: SIAM - SOCIETY FOR INDUSTRIAL AND APPLIED
  • By Emanuel Parzen
  • Price: AUD $178.00
  • Stock: 0 in stock
  • Availability: This book is temporarily out of stock, order will be despatched as soon as fresh stock is received.
  • Local release date: 28/09/1999
  • Format: Paperback (229.00mm X 152.00mm) 343 pages Weight: 489g
  • Categories: Stochastics [PBWL]
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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 phenomema for which stochastic processes provide mathematical models. It introduces the methods or 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. It 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 should continue to find the fundamental and accessible topics explained in this book essential background for their research.
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.
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