Stationary Stochastic Processes

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A01=Georg Lindgren
advanced stochastic process applications
Author_Georg Lindgren
Borel Cantelli Lemma
Borel Sets
Category=PBT
Category=PBWL
Conditional Expectation
Constant Spectral Density
Continuous Sample Paths
correlation analysis
Covariance Function
Cox Process
Distribution Function
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Ergodic Transformations
Finite Dimensional Distributions
Gaussian Process
Half Open Interval
Hilbert Space
level crossing statistics
long-range dependence
Mathematical Science
Ordinary Differential Equation
Probability Theory
Random Field
random field theory
Random Telegraph Signal
reliability modelling
Rice's Formula
Rice’s Formula
Sample Function
Spectral Density
spectral density estimation
Spectral Distribution Function
Stationary Gaussian Process
Stationary Stochastic Process
Stationary Stochastic Processes
Statistics
Stochastic Integrals
Wiener Process

Product details

  • ISBN 9781466557796
  • Weight: 860g
  • Dimensions: 156 x 234mm
  • Publication Date: 01 Oct 2012
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for stationary processes and fields, including a portion on stationary point processes.

Features

  • Presents and illustrates the fundamental correlation and spectral methods for stochastic processes and random fields
  • Explains how the basic theory is used in special applications like detection theory and signal processing, spatial statistics, and reliability
  • Motivates mathematical theory from a statistical model-building viewpoint
  • Introduces a selection of special topics, including extreme value theory, filter theory, long-range dependence, and point processes
  • Provides more than 100 exercises with hints to solutions and selected full solutions

This book covers key topics such as ergodicity, crossing problems, and extremes, and opens the doors to a selection of special topics, like extreme value theory, filter theory, long-range dependence, and point processes, and includes many exercises and examples to illustrate the theory. Precise in mathematical details without being pedantic, Stationary Stochastic Processes: Theory and Applications is for the student with some experience with stochastic processes and a desire for deeper understanding without getting bogged down in abstract mathematics.

Georg Lindgren is with the Centre for Mathematical Sciences, Lund University, Sweden.

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