Long-Range Dependence and Self-Similarity PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Long-Range Dependence and Self-Similarity PDF full book. Access full book title Long-Range Dependence and Self-Similarity by Vladas Pipiras. Download full books in PDF and EPUB format.

Long-Range Dependence and Self-Similarity

Long-Range Dependence and Self-Similarity PDF Author: Vladas Pipiras
Publisher: Cambridge University Press
ISBN: 1107039460
Category : Business & Economics
Languages : en
Pages : 693

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.

Long-Range Dependence and Self-Similarity

Long-Range Dependence and Self-Similarity PDF Author: Vladas Pipiras
Publisher: Cambridge University Press
ISBN: 1107039460
Category : Business & Economics
Languages : en
Pages : 693

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.

Long-Range Dependence and Self-Similarity

Long-Range Dependence and Self-Similarity PDF Author: Vladas Pipiras
Publisher: Cambridge University Press
ISBN: 1108210198
Category : Mathematics
Languages : en
Pages : 693

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.

Theory and Applications of Long-Range Dependence

Theory and Applications of Long-Range Dependence PDF Author: Paul Doukhan
Publisher: Springer Science & Business Media
ISBN: 9780817641689
Category : Mathematics
Languages : en
Pages : 744

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.

Stochastic Processes and Long Range Dependence

Stochastic Processes and Long Range Dependence PDF Author: Gennady Samorodnitsky
Publisher: Springer
ISBN: 3319455753
Category : Mathematics
Languages : en
Pages : 419

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.

Long Range Dependence

Long Range Dependence PDF Author: Gennady Samorodnitsky
Publisher: Now Publishers Inc
ISBN: 1601980906
Category : Mathematics
Languages : en
Pages : 109

Book Description
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-Memory Processes

Long-Memory Processes PDF Author: Jan Beran
Publisher: Springer Science & Business Media
ISBN: 3642355129
Category : Mathematics
Languages : en
Pages : 892

Book Description
Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.

Long-Range Dependent Processes: Theory and Applications

Long-Range Dependent Processes: Theory and Applications PDF Author: Ming Li
Publisher: Frontiers Media SA
ISBN: 2832508502
Category : Science
Languages : en
Pages : 160

Book Description


Markov Processes for Stochastic Modeling

Markov Processes for Stochastic Modeling PDF Author: Oliver Ibe
Publisher: Newnes
ISBN: 0124078397
Category : Mathematics
Languages : en
Pages : 515

Book Description
Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.

Fractals in Engineering

Fractals in Engineering PDF Author: Jacques Lévy-Véhel
Publisher: Springer Science & Business Media
ISBN: 1846280486
Category : Technology & Engineering
Languages : en
Pages : 288

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).

Athens Conference on Applied Probability and Time Series Analysis

Athens Conference on Applied Probability and Time Series Analysis PDF Author: P.M. Robinson
Publisher: Springer Science & Business Media
ISBN: 1461224128
Category : Mathematics
Languages : en
Pages : 443

Book Description
The Athens Conference on Applied Probability and Time Series in 1995 brought together researchers from across the world. The published papers appear in two volumes. Volume II presents papers on time series analysis, many of which were contributed to a meeting in March 1995 partly in honour of E.J. Hannan. The initial paper by P.M. Robinson discusses Ted Hannan's researches and their influence on current work in time series analysis. Other papers discuss methods for finite parameter Gaussian models, time series with infinite variance or stable marginal distribution, frequency domain methods, long range dependent processes, nonstationary processes, and nonlinear time series. The methods presented can be applied in a number of fields such as statistics, applied mathematics, engineering, economics and ecology. The papers include many of the topics of current interest in time series analysis and will be of interest to a wide range of researchers.