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Markov processes:

structure and asymptotic behavior
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Springer-Verlag, 1971 - Mathematics - 268 pages

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Contents

Basic Notions and Illustrations
1
Markov Chains
7
Independent Random Variables
17
Copyright

32 other sections not shown

Common terms and phrases

Assume asymptotic Borel field Borel sets bounded Chapman-Kolmogorov equation characteristic function circle group compact Hausdorff semigroup compact Hausdorff space compact semigroups Consider continuous functions converge Corollary corresponding defined derived distributed random variables distribution function elements equivalent finite number follows given group G Haar measure Hausdorff space idempotent identically distributed random implies independent random variables inequality infinitely divisible infinitely divisible laws integer invariant measure Kolmogorov L2 norm L2 norm condition left ideal Lemma limit theorem mapping Markov chain Markov process Markov property Markovian matrix measurable functions measurable with respect measure zero minimal left nonnegative obtained open sets Poisson positive probability space process Xn purely nondeterministic random walk real numbers real-valued regular probability measure representation result satisfied set function space Q stationary Markov process stationary process stochastic process strongly mixing subgroup subset topology transformation transition function transition probability function uniformly ergodic vector

Bibliographic information

QR code for Markov processes
TitleMarkov processes: structure and asymptotic behavior
Volume 184 of Grundlehren der mathematischen Wissenschaften
Volume 184 of Grundlehren der mathematischen Wissenschaften in Einzeldarstellungen mit besonderer Berücksichtigung der Anwendungsgebiete
Volume 184 of Grundlehren der mathematischen Wissenschaften in Einzeldarstellungen
AuthorMurray Rosenblatt
PublisherSpringer-Verlag, 1971
Original fromUniversity of Minnesota
Digitized8 Oct 2009
ISBN0387054804, 9780387054803
Length268 pages
Subjects ›  › 

Markov processes
Mathematics / Probability & Statistics / General
Stochastic Processes
Stochastic processes
  
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