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Theory And Applications Of Long Range Dependence


Theory And Applications Of Long Range Dependence
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Theory And Applications Of Long Range Dependence


Theory And Applications Of Long Range Dependence
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Author : Paul Doukhan
language : en
Publisher: Birkhäuser
Release Date : 2002-12-13

Theory And Applications Of Long Range Dependence written by Paul Doukhan and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-12-13 with Mathematics categories.


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


Long Range Dependence And Self Similarity
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Author : Vladas Pipiras
language : en
Publisher: Cambridge University Press
Release Date : 2017-04-18

Long Range Dependence And Self Similarity written by Vladas Pipiras and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-18 with Business & Economics categories.


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.



Stochastic Processes And Long Range Dependence


Stochastic Processes And Long Range Dependence
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Author : Gennady Samorodnitsky
language : en
Publisher: Springer
Release Date : 2016-11-09

Stochastic Processes And Long Range Dependence written by Gennady Samorodnitsky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-09 with Mathematics categories.


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
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Author : Gennady Samorodnitsky
language : en
Publisher: Now Publishers Inc
Release Date : 2007

Long Range Dependence written by Gennady Samorodnitsky and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.


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.



Fractals In Engineering


Fractals In Engineering
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Author : Jacques Lévy-Véhel
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-06

Fractals In Engineering written by Jacques Lévy-Véhel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-06 with Technology & Engineering categories.


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).



Stationary Stochastic Processes


Stationary Stochastic Processes
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Author : Georg Lindgren
language : en
Publisher: CRC Press
Release Date : 2012-10-01

Stationary Stochastic Processes written by Georg Lindgren and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-01 with Mathematics categories.


Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for stationary processes and fields, including a portion on stationary point processes. Features Presents and illustrates the fundamental correlation and spectral methods for stochastic processes and random fields Explains how the basic theory is used in special applications like detection theory and signal processing, spatial statistics, and reliability Motivates mathematical theory from a statistical model-building viewpoint Introduces a selection of special topics, including extreme value theory, filter theory, long-range dependence, and point processes Provides more than 100 exercises with hints to solutions and selected full solutions This book covers key topics such as ergodicity, crossing problems, and extremes, and opens the doors to a selection of special topics, like extreme value theory, filter theory, long-range dependence, and point processes, and includes many exercises and examples to illustrate the theory. Precise in mathematical details without being pedantic, Stationary Stochastic Processes: Theory and Applications is for the student with some experience with stochastic processes and a desire for deeper understanding without getting bogged down in abstract mathematics.



Dependence In Probability And Statistics


Dependence In Probability And Statistics
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Author : Patrice Bertail
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-24

Dependence In Probability And Statistics written by Patrice Bertail and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-24 with Mathematics categories.


This book gives an account of recent developments in the field of probability and statistics for dependent data. It covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in times series and random fields. There is a section on statistical estimation problems and specific applications. The book is written as a succession of papers by field specialists, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field.



Statistics For Long Memory Processes


Statistics For Long Memory Processes
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Author : Jan Beran
language : en
Publisher: CRC Press
Release Date : 1994-10-01

Statistics For Long Memory Processes written by Jan Beran and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-10-01 with Mathematics categories.


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.



Dependence In Probability And Statistics


Dependence In Probability And Statistics
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Author : Paul Doukhan
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-23

Dependence In Probability And Statistics written by Paul Doukhan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-23 with Mathematics categories.


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.



Stochastic Models For Geodesy And Geoinformation Science


Stochastic Models For Geodesy And Geoinformation Science
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Author : Frank Neitzel
language : en
Publisher: MDPI
Release Date : 2021-02-12

Stochastic Models For Geodesy And Geoinformation Science written by Frank Neitzel and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-12 with Technology & Engineering categories.


In geodesy and geoinformation science, as well as in many other technical disciplines, it is often not possible to directly determine the desired target quantities. Therefore, the unknown parameters must be linked with the measured values by a mathematical model which consists of the functional and the stochastic models. The functional model describes the geometrical–physical relationship between the measurements and the unknown parameters. This relationship is sufficiently well known for most applications. With regard to the stochastic model, two problem domains of fundamental importance arise: 1. How can stochastic models be set up as realistically as possible for the various geodetic observation methods and sensor systems? 2. How can the stochastic information be adequately considered in appropriate least squares adjustment models? Further questions include the interpretation of the stochastic properties of the computed target values with regard to precision and reliability and the use of the results for the detection of outliers in the input data (measurements). In this Special Issue, current research results on these general questions are presented in ten peer-reviewed articles. The basic findings can be applied to all technical scientific fields where measurements are used for the determination of parameters to describe geometric or physical phenomena.