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Ergodic behavior of Markov processes : with applications to limit theorems /
The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and upper bounds for ergodic rates is presented in the first part of the book, with the focus put on weak ergodic rates, typical for Markov systems with complicated s...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin ; Boston :
Walter de Gruyter GmbH,
[2018]
|
| Colección: | De Gruyter studies in mathematics ;
67. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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|---|---|---|---|
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| 003 | OCoLC | ||
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| 100 | 1 | |a Kulik, Alexei, |e author. | |
| 245 | 1 | 0 | |a Ergodic behavior of Markov processes : |b with applications to limit theorems / |c Alexei Kulik. |
| 264 | 1 | |a Berlin ; |a Boston : |b Walter de Gruyter GmbH, |c [2018] | |
| 264 | 4 | |c ©2018 | |
| 300 | |a 1 online resource (x, 256 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a De Gruyter studies in mathematics, |x 0179-0986 ; |v volume 67 | |
| 504 | |a Includes bibliographical references (pages 249-254) and index. | ||
| 505 | 0 | |a Markov chains with discrete state spaces -- General Markov chains: ergodicity in total variation -- Markov processes with continuous time -- Weak ergodic rates -- The law of large numbers and the central limit theorem -- Functional limit theorems. | |
| 520 | |a The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and upper bounds for ergodic rates is presented in the first part of the book, with the focus put on weak ergodic rates, typical for Markov systems with complicated structure. The second part is devoted to the application of these methods to limit theorems for functionals of Markov processes. The book is aimed at a wide audience with a background in probability and measure theory. Some knowledge of stochastic processes and stochastic differential equations helps in a deeper understanding of specific examples.-- |c Provided by publisher. | ||
| 588 | 0 | |a Online resource; title from PDF title page (EBSCO, viewed February 6, 2018) | |
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Markov processes |v Textbooks. | |
| 650 | 0 | |a Ergodic theory. | |
| 650 | 6 | |a Théorie ergodique. | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Ergodic theory |2 fast | |
| 650 | 7 | |a Markov processes |2 fast | |
| 655 | 7 | |a Textbooks |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Kulik, Alexei. |t Ergodic behavior of Markov processes. |d Berlin : De Gruyter, [2018] |z 9783110458701 |w (OCoLC)1017089483 |
| 776 | 0 | |w (GyWOH)har175017245 | |
| 776 | 0 | |w (GyWOH)har175017246 | |
| 830 | 0 | |a De Gruyter studies in mathematics ; |v 67. | |
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