Stochastic Processes and Long Range Dependence

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Éditeur :

Springer


Collection :

Springer Series in Operations Research and Financial Engineering

Paru le : 2016-11-09

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Description

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 bookhas 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.
Pages
415 pages
Collection
Springer Series in Operations Research and Financial Engineering
Parution
2016-11-09
Marque
Springer
EAN papier
9783319455747
EAN PDF
9783319455754

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
41
Taille du fichier
4065 Ko
Prix
126,59 €
EAN EPUB
9783319455754

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
41
Taille du fichier
5366 Ko
Prix
126,59 €