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Introduction to Stochastic Processes

Gregory F. Lawler
€117.99
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A01=Gregory F. Lawler
advanced stochastic process techniques
Author_Gregory F. Lawler
Brownian Motion
Category=PB
chain
Conditional Expectation
continuous
Continuous Time Markov Chain
Customer Arrives
Discrete Time Markov Chains
Distribution Function
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Extinction Probability
Feynman-Kac formula
Girsanov transformation
Invariant Probability
Invariant Probability Distribution
Invariant Probability Vector
Irreducible Continuous Time Markov Chain
Irreducible Markov Chain
markov
Markov Chain
martingale theory
Optional Sampling Theorem
Positive Recurrent
probability applications
random
Random Variable T1
Recurrent Chain
renewal theory
Residual Life Distribution
Set S1
simple
Simple Random Walk
space
Standard Brownian Motion
state
Stochastic Integral
stochastic modelling
Superharmonic Function
time
Transition Matrix
Uniformly Integrable
variable
walk

Product details

  • ISBN 9781584886518
  • Weight: 476g
  • Dimensions: 156 x 234mm
  • Publication Date: 16 May 2006
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a reasonable level of computer literacy, the ability to write simple programs, and the access to software for linear algebra computations, the author approaches the problems and theorems with a focus on stochastic processes evolving with time, rather than a particular emphasis on measure theory.

For those lacking in exposure to linear differential and difference equations, the author begins with a brief introduction to these concepts. He proceeds to discuss Markov chains, optimal stopping, martingales, and Brownian motion. The book concludes with a chapter on stochastic integration. The author supplies many basic, general examples and provides exercises at the end of each chapter.

New to the Second Edition:

  • Expanded chapter on stochastic integration that introduces modern mathematical finance
  • Introduction of Girsanov transformation and the Feynman-Kac formula
  • Expanded discussion of Itô's formula and the Black-Scholes formula for pricing options
  • New topics such as Doob's maximal inequality and a discussion on self similarity in the chapter on Brownian motion

    Applicable to the fields of mathematics, statistics, and engineering as well as computer science, economics, business, biological science, psychology, and engineering, this concise introduction is an excellent resource both for students and professionals.
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    About Gregory F. Lawler
    Greogory F. Lawler

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