Long-Memory Processes
Long-Memory Processes

Author: Jan Beran

Publisher: Springer Science & Business Media

Published: 2013-05-14

Total Pages: 892

ISBN-13: 3642355129

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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.

Cyclostationarity: Theory and Methods – IV
Cyclostationarity: Theory and Methods – IV

Author: Fakher Chaari

Publisher: Springer

Published: 2019-07-31

Total Pages: 234

ISBN-13: 3030225291

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This book gathers contributions presented at the 10th Workshop on Cyclostationary Systems and Their Applications, held in Gródek nad Dunajcem, Poland in February 2017. It includes twelve interesting papers covering current topics related to both cyclostationary and general non stationary processes. Moreover, this book, which covers both theoretical and practical issues, offers a practice-oriented guide to the analysis of data sets with non-stationary behavior and a bridge between basic and applied research on nonstationary processes. It provides students, researchers and professionals with a timely guide on cyclostationary systems, nonstationary processes and relevant engineering applications.

Cyclostationarity: Theory and Methods III
Cyclostationarity: Theory and Methods III

Author: Fakher Chaari

Publisher: Springer

Published: 2017-02-25

Total Pages: 261

ISBN-13: 3319514458

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This book gathers contributions presented at the 9th Workshop on Cyclostationary Systems and Their Applications, held in Gródek nad Dunajcem, Poland in February 2016. It includes both theory-oriented and practice-oriented chapters. The former focus on heavy-tailed time series and processes, PAR models, rational spectra for PARMA processes, covariance invariant analysis, change point problems, and subsampling for time series, as well as the fraction-of-time approach, GARMA models and weak dependence. In turn, the latter report on case studies of various mechanical systems, and on stochastic and statistical methods, especially in the context of damage detection. The book provides students, researchers and professionals with a timely guide to cyclostationary systems, nonstationary processes and relevant engineering applications.

In Extremis
In Extremis

Author: Jürgen Kropp

Publisher: Springer Science & Business Media

Published: 2010-11-03

Total Pages: 329

ISBN-13: 3642148638

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The book addresses a weakness of current methodologies used in extreme value assessment, i.e. the assumption of stationarity, which is not given in reality. With respect to this issue a lot of new developed technologies are presented, i.e. influence of trends vs. internal correlations, quantitative uncertainty assessments, etc. The book not only focuses on artificial time series data, but has a close link to empirical measurements, in order to make the suggested methodologies applicable for practitioners in water management and meteorology.

ESSE 2017
ESSE 2017

Author: Yong Wang

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2017-10-23

Total Pages: 924

ISBN-13: 3110540045

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Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017.

Climate Time Series Analysis
Climate Time Series Analysis

Author: Manfred Mudelsee

Publisher: Springer

Published: 2014-06-27

Total Pages: 477

ISBN-13: 3319044508

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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. “....comprehensive mathematical and statistical summary of time-series analysis techniques geared towards climate applications...accessible to readers with knowledge of college-level calculus and statistics.” (Computers and Geosciences) “A key part of the book that separates it from other time series works is the explicit discussion of time uncertainty...a very useful text for those wishing to understand how to analyse climate time series.” (Journal of Time Series Analysis) “...outstanding. One of the best books on advanced practical time series analysis I have seen.” (David J. Hand, Past-President Royal Statistical Society)

Time Series Analysis and Its Applications
Time Series Analysis and Its Applications

Author: Robert H. Shumway

Publisher: Springer

Published: 2017-04-25

Total Pages: 567

ISBN-13: 3319524526

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The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods. This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.

Time Series Analysis with Long Memory in View
Time Series Analysis with Long Memory in View

Author: Uwe Hassler

Publisher: John Wiley & Sons

Published: 2018-10-30

Total Pages: 288

ISBN-13: 1119470404

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Provides a simple exposition of the basic time series material, and insights into underlying technical aspects and methods of proof Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation. Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests. Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book: Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs Contains many new results on long memory processes which have not appeared in previous and existing textbooks Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory Contains 25 illustrative figures as well as lists of notations and acronyms Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.