Statistics for Long-Memory Processes

Author: Jan Beran

Publisher: CRC Press

ISBN: 9780412049019

Category: Mathematics

Page: 315

View: 6743

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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.

Large Sample Inference for Long Memory Processes

Author: Liudas Giraitis,Hira L Koul,Donatas Surgailis

Publisher: World Scientific Publishing Company

ISBN: 1911299387

Category: Mathematics

Page: 596

View: 7783

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Box and Jenkins (1970) made the idea of obtaining a stationary time series by differencing the given, possibly nonstationary, time series popular. Numerous time series in economics are found to have this property. Subsequently, Granger and Joyeux (1980) and Hosking (1981) found examples of time series whose fractional difference becomes a short memory process, in particular, a white noise, while the initial series has unbounded spectral density at the origin, i.e. exhibits long memory. Further examples of data following long memory were found in hydrology and in network traffic data while in finance the phenomenon of strong dependence was established by dramatic empirical success of long memory processes in modeling the volatility of the asset prices and power transforms of stock market returns. At present there is a need for a text from where an interested reader can methodically learn about some basic asymptotic theory and techniques found useful in the analysis of statistical inference procedures for long memory processes. This text makes an attempt in this direction. The authors provide in a concise style a text at the graduate level summarizing theoretical developments both for short and long memory processes and their applications to statistics. The book also contains some real data applications and mentions some unsolved inference problems for interested researchers in the field. Sample Chapter(s) Chapter 1: Introduction (152 KB) Chapter 3: Long Memory Processes (253 KB) Chapter 7: Parametric Models (635 KB) Request Inspection Copy Contents:IntroductionSome PreliminariesLong Memory ProcessesLimit Theory for SumsProperties of the DFT and the PeriodogramAsymptotic Theory for Quadratic FormsParametric ModelsEstimationElementary Inference ProblemsEmpirical ProcessesRegression ModelsNon-parametric RegressionModel DiagnosticsAppendix Readership: Students and professionals in statistics, econometrics and finance.

Long-Memory Processes

Probabilistic Properties and Statistical Methods

Author: Jan Beran,Yuanhua Feng,Sucharita Ghosh,Rafal Kulik

Publisher: Springer Science & Business Media

ISBN: 3642355129

Category: Mathematics

Page: 884

View: 8104

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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-Memory Processes

Probabilistic Properties and Statistical Methods

Author: Jan Beran,Yuanhua Feng,Sucharita Ghosh,Rafal Kulik

Publisher: Springer Science & Business Media

ISBN: 3642355129

Category: Mathematics

Page: 884

View: 7668

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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-Memory Time Series

Theory and Methods

Author: Wilfredo Palma

Publisher: John Wiley & Sons

ISBN: 0470131454

Category: Mathematics

Page: 304

View: 6068

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A self-contained, contemporary treatment of the analysis of long-range dependent data Long-Memory Time Series: Theory and Methods provides an overview of the theory and methods developed to deal with long-range dependent data and describes the applications of these methodologies to real-life time series. Systematically organized, it begins with the foundational essentials, proceeds to the analysis of methodological aspects (Estimation Methods, Asymptotic Theory, Heteroskedastic Models, Transformations, Bayesian Methods, and Prediction), and then extends these techniques to more complex data structures. To facilitate understanding, the book: Assumes a basic knowledge of calculus and linear algebra and explains the more advanced statistical and mathematical concepts Features numerous examples that accelerate understanding and illustrate various consequences of the theoretical results Proves all theoretical results (theorems, lemmas, corollaries, etc.) or refers readers to resources with further demonstration Includes detailed analyses of computational aspects related to the implementation of the methodologies described, including algorithm efficiency, arithmetic complexity, CPU times, and more Includes proposed problems at the end of each chapter to help readers solidify their understanding and practice their skills A valuable real-world reference for researchers and practitioners in time series analysis, economerics, finance, and related fields, this book is also excellent for a beginning graduate-level course in long-memory processes or as a supplemental textbook for those studying advanced statistics, mathematics, economics, finance, engineering, or physics. A companion Web site is available for readers to access the S-Plus and R data sets used within the text.

Time Series with Long Memory

Author: Peter M. Robinson

Publisher: Oxford University Press, USA

ISBN: 9780199257300

Category: Business & Economics

Page: 382

View: 613

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Long memory time series are characterised by a strong dependence between distant events. In this book, various methods and their theoretical properties are discussed with empirical applications. The methods constitute a very flexible approach to analysing time series data arising in economics, finance and other fields.

Theory and Engineering of Complex Systems and Dependability

Proceedings of the Tenth International Conference on Dependability and Complex Systems DepCoS-RELCOMEX, June 29 – July 3 2015, Brunów, Poland

Author: Wojciech Zamojski,Jacek Mazurkiewicz,Jarosław Sugier,Tomasz Walkowiak,Janusz Kacprzyk

Publisher: Springer

ISBN: 3319192167

Category: Computers

Page: 604

View: 8272

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Building upon a long tradition of scientifi c conferences dealing with problems of reliability in technical systems, in 2006 Department of Computer Engineering at Wrocław University of Technology established DepCoS-RELCOMEX series of events in order to promote a comprehensive approach to evaluation of system performability which is now commonly called dependability. Contemporary complex systems integrate variety of technical, information, soft ware and human (users, administrators and management) resources. Their complexity comes not only from involved technical and organizational structures but mainly from complexity of information processes that must be implemented in specific operational environment (data processing, monitoring, management, etc.). In such a case traditional methods of reliability evaluation focused mainly on technical levels are insufficient and more innovative, multidisciplinary methods of dependability analysis must be applied. Selection of submissions for these proceedings exemplify diversity of topics that must be included in such analyses: tools, methodologies and standards for modelling, design and simulation of the systems, security and confidentiality in information processing, specific issues of heterogeneous, today often wireless, computer networks, or management of transportation networks. In addition, this edition of the conference hosted the 5th CrISS-DESSERT Workshop devoted to the problems of security and safety in critical information systems.

Fractals in Engineering

New Trends in Theory and Applications

Author: Jacques Lévy-Véhel,Evelyne Lutton

Publisher: Springer Science & Business Media

ISBN: 1846280486

Category: Technology & Engineering

Page: 290

View: 1713

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Empirical Process Techniques for Dependent Data

Author: Herold Dehling,Thomas Mikosch,Michael Sörensen

Publisher: Springer Science & Business Media

ISBN: 1461200997

Category: Mathematics

Page: 383

View: 7350

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Empirical process techniques for independent data have been used for many years in statistics and probability theory. These techniques have proved very useful for studying asymptotic properties of parametric as well as non-parametric statistical procedures. Recently, the need to model the dependence structure in data sets from many different subject areas such as finance, insurance, and telecommunications has led to new developments concerning the empirical distribution function and the empirical process for dependent, mostly stationary sequences. This work gives an introduction to this new theory of empirical process techniques, which has so far been scattered in the statistical and probabilistic literature, and surveys the most recent developments in various related fields. Key features: A thorough and comprehensive introduction to the existing theory of empirical process techniques for dependent data * Accessible surveys by leading experts of the most recent developments in various related fields * Examines empirical process techniques for dependent data, useful for studying parametric and non-parametric statistical procedures * Comprehensive bibliographies * An overview of applications in various fields related to empirical processes: e.g., spectral analysis of time-series, the bootstrap for stationary sequences, extreme value theory, and the empirical process for mixing dependent observations, including the case of strong dependence. To date this book is the only comprehensive treatment of the topic in book literature. It is an ideal introductory text that will serve as a reference or resource for classroom use in the areas of statistics, time-series analysis, extreme value theory, point process theory, and applied probability theory. Contributors: P. Ango Nze, M.A. Arcones, I. Berkes, R. Dahlhaus, J. Dedecker, H.G. Dehling,

Long Range Dependence

Author: Gennady Samorodnitsky

Publisher: Now Publishers Inc

ISBN: 1601980906

Category: Mathematics

Page: 99

View: 4287

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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.

Discrete Time Series, Processes, and Applications in Finance

Author: Gilles Zumbach

Publisher: Springer Science & Business Media

ISBN: 3642317421

Category: Mathematics

Page: 322

View: 8007

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Most financial and investment decisions are based on considerations of possible future changes and require forecasts on the evolution of the financial world. Time series and processes are the natural tools for describing the dynamic behavior of financial data, leading to the required forecasts. This book presents a survey of the empirical properties of financial time series, their descriptions by means of mathematical processes, and some implications for important financial applications used in many areas like risk evaluation, option pricing or portfolio construction. The statistical tools used to extract information from raw data are introduced. Extensive multiscale empirical statistics provide a solid benchmark of stylized facts (heteroskedasticity, long memory, fat-tails, leverage...), in order to assess various mathematical structures that can capture the observed regularities. The author introduces a broad range of processes and evaluates them systematically against the benchmark, summarizing the successes and limitations of these models from an empirical point of view. The outcome is that only multiscale ARCH processes with long memory, discrete multiplicative structures and non-normal innovations are able to capture correctly the empirical properties. In particular, only a discrete time series framework allows to capture all the stylized facts in a process, whereas the stochastic calculus used in the continuum limit is too constraining. The present volume offers various applications and extensions for this class of processes including high-frequency volatility estimators, market risk evaluation, covariance estimation and multivariate extensions of the processes. The book discusses many practical implications and is addressed to practitioners and quants in the financial industry, as well as to academics, including graduate (Master or PhD level) students. The prerequisites are basic statistics and some elementary financial mathematics.

Climate Time Series Analysis

Classical Statistical and Bootstrap Methods

Author: Manfred Mudelsee

Publisher: Springer Science & Business Media

ISBN: 9789048194827

Category: Science

Page: 474

View: 4438

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Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.

Theory and Applications of Long-Range Dependence

Author: Paul Doukhan,George Oppenheim,Murad S. Taqqu

Publisher: Springer Science & Business Media

ISBN: 9780817641689

Category: Business & Economics

Page: 719

View: 2919

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Time series research has been an area of considerable research activity over the past several decades. The essential ingredient --- the notion of time-dependence --- is required for measuring and then accurately predicting data to construct suitable models for diverse phenomena. This fairly self-contained volume, written by leading experts in their respective fields, especially focuses on the theoretical concepts, methodologies, and practical applications pertaining to self-similar processes and long-range dependent phenomena. Graduate students, researchers, and professionals in industry will benefit from the book.

Advances in Quantitative Asset Management

Author: Christian Dunis

Publisher: Springer Science & Business Media

ISBN: 9780792377788

Category: Business & Economics

Page: 342

View: 9020

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Advances in Quantitative Asset Management contains selected articles which, for the most part, were presented at the `Forecasting Financial Markets' Conference. `Forecasting Financial Markets' is an international conference on quantitative finance which is held in London in May every year. Since its inception in 1994, the conference has grown in scope and stature to become a key international meeting point for those interested in quantitative finance, with the participation of prestigious academic and research institutions from all over the world, including major central banks and quantitative fund managers. The editor has chosen to concentrate on advances in quantitative asset management and, accordingly, the papers in this book are organized around two major themes: advances in asset allocation and portfolio management, and modelling risk, return and correlation.

Processes with Long-Range Correlations

Theory and Applications

Author: Govindan Rangarajan,Mingzhou Ding

Publisher: Springer

ISBN: 3540448322

Category: Medical

Page: 398

View: 2735

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Processes with long range correlations occur in a wide variety of fields ranging from physics and biology to economics and finance. This book, suitable for both graduate students and specialists, brings the reader up to date on this rapidly developing field. A distinguished group of experts have been brought together to provide a comprehensive and well-balanced account of basic notions and recent developments. The book is divided into two parts. The first part deals with theoretical developments in the area. The second part comprises chapters dealing primarily with three major areas of application: anomalous diffusion, economics and finance, and biology (especially neuroscience).

Modeling Financial Time Series with S-PLUS®

Author: Eric Zivot,Jiahui Wang

Publisher: Springer Science & Business Media

ISBN: 9780387323480

Category: Business & Economics

Page: 998

View: 9727

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This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. It is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This edition covers S+FinMetrics 2.0 and includes new chapters.

Applied Time Series Analysis

Author: Wayne A. Woodward,Henry L. Gray,Alan C Elliott

Publisher: CRC Press

ISBN: 1439897697

Category: Mathematics

Page: 564

View: 3021

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Virtually any random process developing chronologically can be viewed as a time series. In economics, closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis includes examples across a variety of fields, develops theory, and provides software to address time series problems in a broad spectrum of fields. The authors organize the information in such a format that graduate students in applied science, statistics, and economics can satisfactorily navigate their way through the book while maintaining mathematical rigor. One of the unique features of Applied Time Series Analysis is the associated software, GW-WINKS, designed to help students easily generate realizations from models and explore the associated model and data characteristics. The text explores many important new methodologies that have developed in time series, such as ARCH and GARCH processes, time varying frequencies (TVF), wavelets, and more. Other programs (some written in R and some requiring S-plus) are available on an associated website for performing computations related to the material in the final four chapters.

Proceedings of the Third International Conference on Wavelet Analysis and Its Applications (WAA)

Chongqing, PR China, 29-31 May 2003

Author: Jian Ping Li

Publisher: World Scientific

ISBN: 9812796762

Category: Electronic books

Page: 1056

View: 9217

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This book captures the essence of the current state of research in wavelet analysis and its applications, and identifies the changes and opportunities OCo both current and future OCo in the field. Distinguished researchers such as Prof John Daugman from Cambridge University and Prof Victor Wickerhauser from Washington University present their research papers. Contents: Volume 1: Accelerating Convergence of Monte Carlo Simulations and Measuring Weak Biosignals Using Wavelet Threshold Denoising (M V Wickerhauser); One of Image Compression Methods Based on Biorthogonal Wavelet Transform and LBG Algorithm (J Lin et al.); A Video Watermarking Algorithm Using Fast Wavelet (J Zhang et al.); Structural and Geometric Characteristics of Sets of Convergence and Divergence of Multiple Fourier Series of Functions which Equal Zero on Some Set (I L Bloshanskii); Sequence Images Data Fusion Based on Wavelet Transform Approach (H Tao et al.); Radar Detection of Minimum Altitude Flying Targets Based on Wavelet Transforms (H Li et al.); Precursors of Engine Failures Revealed by Wavelet Analysis (I M Dremin); Volume 2: Demodulation by Complex-Valued Wavelets for Stochastic Pattern Recognition: How Iris Recognition Works (J Daugman); Wavelets and Image Compression (V A Nechitailo); Fast Wavelet-Based Video Codec and its Application in an IP Version 6-Ready Serverless Videoconferencing (H L Cycon et al.); On a Class of Optimal Wavelets (N A Strelkov & V L Dol''nikov); A Wavelet-Based Digital Watermarking Algorithm (H Q Sun et al.); Research of the Gyro Signal De-Noising Method Based on Stationary Wavelets Transform (J Guo et al.); Adaptive De-Noising of Low SNR Signals (D Isar & A Isar); Analysis of the DLA-Process with Gravitational Interaction of Particles and Growing Cluster (A Loskutov et al.); and other papers. Readership: Graduate students, academics and researchers in computer science and engineering."

Mathematical Foundations of Time Series Analysis

A Concise Introduction

Author: Jan Beran

Publisher: Springer

ISBN: 3319743805

Category: Mathematics

Page: 307

View: 822

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This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.