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Stochastic Processes and Long Range Dependence

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Release : 2016-11-09
Genre : Mathematics
Kind : eBook
Book Rating : 753/5 ( reviews)

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Book Synopsis Stochastic Processes and Long Range Dependence by : Gennady Samorodnitsky

Download or read book Stochastic Processes and Long Range Dependence written by Gennady Samorodnitsky. This book was released on 2016-11-09. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Theory and Applications of Long-Range Dependence

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Release : 2002-12-13
Genre : Mathematics
Kind : eBook
Book Rating : 689/5 ( reviews)

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Book Synopsis Theory and Applications of Long-Range Dependence by : Paul Doukhan

Download or read book Theory and Applications of Long-Range Dependence written by Paul Doukhan. This book was released on 2002-12-13. Available in PDF, EPUB and Kindle. Book excerpt: The area of data analysis has been greatly affected by our computer age. For example, the issue of collecting and storing huge data sets has become quite simplified and has greatly affected such areas as finance and telecommunications. Even non-specialists try to analyze data sets and ask basic questions about their structure. One such question is whether one observes some type of invariance with respect to scale, a question that is closely related to the existence of long-range dependence in the data. This important topic of long-range dependence is the focus of this unique work, written by a number of specialists on the subject. The topics selected should give a good overview from the probabilistic and statistical perspective. Included will be articles on fractional Brownian motion, models, inequalities and limit theorems, periodic long-range dependence, parametric, semiparametric, and non-parametric estimation, long-memory stochastic volatility models, robust estimation, and prediction for long-range dependence sequences. For those graduate students and researchers who want to use the methodology and need to know the "tricks of the trade," there will be a special section called "Mathematical Techniques." Topics in the first part of the book are covered from probabilistic and statistical perspectives and include fractional Brownian motion, models, inequalities and limit theorems, periodic long-range dependence, parametric, semiparametric, and non-parametric estimation, long-memory stochastic volatility models, robust estimation, prediction for long-range dependence sequences. The reader is referred to more detailed proofs if already found in the literature. The last part of the book is devoted to applications in the areas of simulation, estimation and wavelet techniques, traffic in computer networks, econometry and finance, multifractal models, and hydrology. Diagrams and illustrations enhance the presentation. Each article begins with introductory background material and is accessible to mathematicians, a variety of practitioners, and graduate students. The work serves as a state-of-the art reference or graduate seminar text.

Long-Range Dependence and Self-Similarity

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Release : 2017-04-18
Genre : Business & Economics
Kind : eBook
Book Rating : 460/5 ( reviews)

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Book Synopsis Long-Range Dependence and Self-Similarity by : Vladas Pipiras

Download or read book Long-Range Dependence and Self-Similarity written by Vladas Pipiras. This book was released on 2017-04-18. Available in PDF, EPUB and Kindle. Book excerpt: A modern and rigorous introduction to long-range dependence and self-similarity, complemented by numerous more specialized up-to-date topics in this research area.

Long Range Dependence

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Author :
Release : 2007
Genre : Mathematics
Kind : eBook
Book Rating : 906/5 ( reviews)

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Book Synopsis Long Range Dependence by : Gennady Samorodnitsky

Download or read book Long Range Dependence written by Gennady Samorodnitsky. This book was released on 2007. Available in PDF, EPUB and Kindle. Book excerpt: Long Range Dependence is a wide ranging survey of the ideas, models and techniques associated with the notion of long memory. It will serve as an invaluable reference source for researchers studying long range dependence, for those building long memory models, and for people who are trying to detect the possible presence of long memory in data.

Long-Range Dependence and Self-Similarity

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Author :
Release : 2017-04-18
Genre : Mathematics
Kind : eBook
Book Rating : 198/5 ( reviews)

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Book Synopsis Long-Range Dependence and Self-Similarity by : Vladas Pipiras

Download or read book Long-Range Dependence and Self-Similarity written by Vladas Pipiras. This book was released on 2017-04-18. Available in PDF, EPUB and Kindle. Book excerpt: This modern and comprehensive guide to long-range dependence and self-similarity starts with rigorous coverage of the basics, then moves on to cover more specialized, up-to-date topics central to current research. These topics concern, but are not limited to, physical models that give rise to long-range dependence and self-similarity; central and non-central limit theorems for long-range dependent series, and the limiting Hermite processes; fractional Brownian motion and its stochastic calculus; several celebrated decompositions of fractional Brownian motion; multidimensional models for long-range dependence and self-similarity; and maximum likelihood estimation methods for long-range dependent time series. Designed for graduate students and researchers, each chapter of the book is supplemented by numerous exercises, some designed to test the reader's understanding, while others invite the reader to consider some of the open research problems in the field today.

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