Stochastic Processes

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A01=Peter Smith
A01=Peter Watts Jones
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Asymmetric Walk
Author_Peter Smith
Author_Peter Watts Jones
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Brownian Motion
Category1=Non-Fiction
Category=PBT
Category=PBWL
Conditional Expectation
Continuous Random Variable
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Cumulative Distribution Function
Death Process
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Differential Difference Equations
eq_isMigrated=2
Exponential Distribution
Failure Rate Function
function
gambler's
Gambler's Ruin
Gambler's Ruin Problem
Gambler’s Ruin
Gambler’s Ruin Problem
Geometric Brownian Motion
Initial Population Size
Inter-arrival Times
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law
Ordinary Differential Equation
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Peter Smith
Peter W. Jones
poisson
Poisson Process
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probability
Probability Generating Function
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random
Random Variable
Random Walk
Reliability Function
Simple Birth
Single Server Queue
softlaunch
Standard Brownian Motion
symmetric
Symmetric Random Walk
total
variable
walk
Wiener Process

Product details

  • ISBN 9781498778114
  • Weight: 521g
  • Dimensions: 156 x 234mm
  • Publication Date: 16 Oct 2017
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
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Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general population models, and present an extended discussion on the analysis of associated stationary processes in queues.

The book also explores reliability and other random processes, such as branching, martingales, and simple epidemics. A new chapter describing Brownian motion, where the outcomes are continuously observed over continuous time, is included. Further applications, worked examples and problems, and biographical details have been added to this edition. Much of the text has been reworked. The appendix contains key results in probability for reference.

This concise, updated book makes the material accessible, highlighting simple applications and examples. A solutions manual with fully worked answers of all end-of-chapter problems, and Mathematica® and R programs illustrating many processes discussed in the book, can be downloaded from crcpress.com.

Peter W. Jones is a professor and Pro Vice Chancellor for Research and Enterprise at Keele University in Staffordshire, UK.

Peter Smith is a Professor Emeritus in the School of Computing and Mathematics at Keele University in Staffordshire, UK.