<p>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 a
Stochastic Processes and Long Range Dependence
β Scribed by Gennady Samorodnitsky (auth.)
- Publisher
- Springer International Publishing
- Year
- 2016
- Tongue
- English
- Leaves
- 419
- Series
- Springer Series in Operations Research and Financial Engineering
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 authorβs 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.
β¦ Table of Contents
Front Matter....Pages i-xi
Stationary Processes....Pages 1-26
Elements of Ergodic Theory of Stationary Processes and Strong Mixing....Pages 27-71
Infinitely Divisible Processes....Pages 73-132
Heavy Tails....Pages 133-173
Introduction to Long-Range Dependence....Pages 175-191
Second-Order Theory of Long-Range Dependence....Pages 193-228
Fractionally Differenced and Fractionally Integrated Processes....Pages 229-246
Self-Similar Processes....Pages 247-283
Long-Range Dependence as a Phase Transition....Pages 285-361
Appendix....Pages 363-404
Back Matter....Pages 405-415
β¦ Subjects
Probability Theory and Stochastic Processes;Measure and Integration;Dynamical Systems and Ergodic Theory
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