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Author: Paul Doukhan
Publisher: Birkhauser
ISBN:
Category : Brownian motion processes
Languages : en
Pages : 744
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Book Description
Long-range dependence is an important topic in the rapidly developing area of data analysis. This unique collection presents self-contained chapters written by specialists that present a comprehensive overview of the subject from the probabilistic and statistical perspective. A special section is devoted solely to mathematical techniques, and diagrams and illustrations enhance the presentation. The book discusses a number of applications from various areas including simulation and estimation, wavelets and computer networks, and econometrics and finance. Copyright © Libri GmbH. All rights reserved.
Author: Paul Doukhan
Publisher: Birkhauser
ISBN:
Category : Brownian motion processes
Languages : en
Pages : 744
Get Book Here
Book Description
Long-range dependence is an important topic in the rapidly developing area of data analysis. This unique collection presents self-contained chapters written by specialists that present a comprehensive overview of the subject from the probabilistic and statistical perspective. A special section is devoted solely to mathematical techniques, and diagrams and illustrations enhance the presentation. The book discusses a number of applications from various areas including simulation and estimation, wavelets and computer networks, and econometrics and finance. Copyright © Libri GmbH. All rights reserved.
Author: Paul Doukhan
Publisher: Springer Science & Business Media
ISBN: 9780817641689
Category : Mathematics
Languages : en
Pages : 744
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Book Description
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.
Author: Gennady Samorodnitsky
Publisher: Springer
ISBN: 3319455753
Category : Mathematics
Languages : en
Pages : 419
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Book 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 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.
Author: Vladas Pipiras
Publisher: Cambridge University Press
ISBN: 1107039460
Category : Business & Economics
Languages : en
Pages : 693
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Book Description
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.
Author: Jérome Dedecker
Publisher: Springer Science & Business Media
ISBN: 038769952X
Category : Mathematics
Languages : en
Pages : 326
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Book Description
This book develops Doukhan/Louhichi's 1999 idea to measure asymptotic independence of a random process. The authors, who helped develop this theory, propose examples of models fitting such conditions: stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Applications are still needed to develop a method of analysis for nonlinear times series, and this book provides a strong basis for additional studies.
Author: Vladas Pipiras
Publisher: Cambridge University Press
ISBN: 1108210198
Category : Mathematics
Languages : en
Pages : 693
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Book Description
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.
Author: Jacques Lévy-Véhel
Publisher: Springer Science & Business Media
ISBN: 1846280486
Category : Technology & Engineering
Languages : en
Pages : 288
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Book Description
The application of fractals in the engineering sciences is evolving swiftly and the editors have turned to Springer for the third time to bring you the latest research emerging from the rapid growth in techniques available for the employment of the ideas of fractals and complexity to a variety of disciplines in and associated with the engineering field. The strong potential of this research can be seen in real industrial situations with recent progress being made in areas such as chemical engineering, internet traffic, physics and finance. Image processing continues to be a major field of application for fractal analysis and is well-represented here. It is important to note that the applications models are presented with a firm basis in theoretical argument, the qualitative observation of fractal phenomena no longer being sufficient. Consisting of papers written by a world-wide pool of experts, the multidisciplinary approach of this third volume will be of particular interest to industrial researchers and practitioners as well as to academics from many backgrounds. Fractals in Engineering: New Trends in Theory and Applications continues the publication of engineering-related research in fractal techniques begun in Fractals in Engineering and Fractals: Theory and Applications in Engineering (Springer London 1997 and 1999).
Author: Ming Li
Publisher: Frontiers Media SA
ISBN: 2832508502
Category : Science
Languages : en
Pages : 160
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Book Description
Author: Paul Doukhan
Publisher: Springer Science & Business Media
ISBN: 3642141048
Category : Mathematics
Languages : en
Pages : 222
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Book Description
This account of recent works on weakly dependent, long memory and multifractal processes introduces new dependence measures for studying complex stochastic systems and includes other topics such as the dependence structure of max-stable processes.
Author: Jan Beran
Publisher: CRC Press
ISBN: 9780412049019
Category : Mathematics
Languages : en
Pages : 336
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Book Description
Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications and provides an integrated perspective of both theory and practice. This book explores data sets from a wide range of disciplines, such as hydrology, climatology, telecommunications engineering, and high-precision physical measurement. The data sets are conveniently compiled in the index, and this allows readers to view statistical approaches in a practical context. Statistical Methods for Long Term Memory Processes also supplies S-PLUS programs for the major methods discussed. This feature allows the practitioner to apply long memory processes in daily data analysis. For newcomers to the area, the first three chapters provide the basic knowledge necessary for understanding the remainder of the material. To promote selective reading, the author presents the chapters independently. Combining essential methodologies with real-life applications, this outstanding volume is and indispensable reference for statisticians and scientists who analyze data with long-range dependence.
