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Stochastic processes and long range ...

Samorodnitsky, Gennady.

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Stochastic processes and long range dependence

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic processes and long range dependence/ by Gennady Samorodnitsky.
Author:	Samorodnitsky, Gennady.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xi, 415 p. :ill., digital ;24 cm.
[NT 15003449]:	Preface -- Stationary Processes -- Ergodic Theory of Stationary Processes -- Infinitely Divisible Processes -- Heavy Tails -- Hurst Phenomenon -- Second-order Theory -- Fractionally Integrated Processes -- Self-similar Processes -- Long Range Dependence as a Phase Transition -- Appendix.
Contained By:	Springer eBooks
Subject:	Stochastic processes. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-45575-4
ISBN:	9783319455754

Stochastic processes and long range dependence
Samorodnitsky, Gennady.

Stochastic processes and long range dependence[electronic resource] /by Gennady Samorodnitsky. - Cham :Springer International Publishing :2016. - xi, 415 p. :ill., digital ;24 cm. - Springer series in operations research and financial engineering,1431-8598. - Springer series in operations research and financial engineering..

Preface -- Stationary Processes -- Ergodic Theory of Stationary Processes -- Infinitely Divisible Processes -- Heavy Tails -- Hurst Phenomenon -- Second-order Theory -- Fractionally Integrated Processes -- Self-similar Processes -- Long Range Dependence as a Phase Transition -- Appendix.

This monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory) The text is organized around the probabilistic properties of stationary processes that are important for determining the presence or absence of long memory. The first few chapters serve as an overview of the general theory of stochastic processes which gives the reader sufficient background, language, and models for the subsequent discussion of long memory. The later chapters devoted to long memory begin with an introduction to the subject along with a brief history of its development, followed by a presentation of what is currently the best known approach, applicable to stationary processes with a finite second moment. The book concludes with a chapter devoted to the author's own, less standard, point of view of long memory as a phase transition, and even includes some novel results. Most of the material in the book has not previously been published in a single self-contained volume, and can be used for a one- or two-semester graduate topics course. It is complete with helpful exercises and an appendix which describes a number of notions and results belonging to the topics used frequently throughout the book, such as topological groups and an overview of the Karamata theorems on regularly varying functions.

ISBN: 9783319455754

Standard No.: 10.1007/978-3-319-45575-4doiSubjects--Topical Terms:

520663
Stochastic processes.

LC Class. No.: QA274

Dewey Class. No.: 519.23

Stochastic processes and long range dependence
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100 1 $a Samorodnitsky, Gennady. $3 686263
245 1 0 $a Stochastic processes and long range dependence $h [electronic resource] / $c by Gennady Samorodnitsky.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xi, 415 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer series in operations research and financial engineering, $x 1431-8598
505 0 $a Preface -- Stationary Processes -- Ergodic Theory of Stationary Processes -- Infinitely Divisible Processes -- Heavy Tails -- Hurst Phenomenon -- Second-order Theory -- Fractionally Integrated Processes -- Self-similar Processes -- Long Range Dependence as a Phase Transition -- Appendix.
520 $a This monograph is a gateway for researchers and graduate students to explore the profound, yet subtle, world of long-range dependence (also known as long memory) The text is organized around the probabilistic properties of stationary processes that are important for determining the presence or absence of long memory. The first few chapters serve as an overview of the general theory of stochastic processes which gives the reader sufficient background, language, and models for the subsequent discussion of long memory. The later chapters devoted to long memory begin with an introduction to the subject along with a brief history of its development, followed by a presentation of what is currently the best known approach, applicable to stationary processes with a finite second moment. The book concludes with a chapter devoted to the author's own, less standard, point of view of long memory as a phase transition, and even includes some novel results. Most of the material in the book has not previously been published in a single self-contained volume, and can be used for a one- or two-semester graduate topics course. It is complete with helpful exercises and an appendix which describes a number of notions and results belonging to the topics used frequently throughout the book, such as topological groups and an overview of the Karamata theorems on regularly varying functions.
650 0 $a Stochastic processes. $3 520663
650 1 4 $a Mathematics. $3 515831
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
650 2 4 $a Measure and Integration. $3 891263
650 2 4 $a Dynamical Systems and Ergodic Theory. $3 891276
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