Large Sample Inference For Long Memory Processes
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Large Sample Inference For Long Memory Processes
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Author : Liudas Giraitis
language : en
Publisher:
Release Date : 2012
Large Sample Inference For Long Memory Processes written by Liudas Giraitis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Mathematics categories.
A discrete-time stationary stochastic process with finite variance is said to have long memory if its autocorrelations tend to zero hyperbolically in the lag, i.e. like a power of the lag, as the lag tends to infinity. The absolute sum of autocorrelations of such processes diverges and their spectral density at the origin is unbounded. This is unlike the so-called weakly dependent processes, where autocorrelations tend to zero exponentially fast and the spectral density is bounded at the origin. In a long memory process, the dependence between the current observation and the one at a distant future is persistent; whereas in the weakly dependent processes, these observations are approximately independent. This fact alone is enough to warn a person about the validity of the classical inference procedures based on the square root of the sample size standardization when data are generated by a long-term memory process.The aim of this volume is to provide a text at the graduate level from which one can learn, in a concise fashion, some basic theory and techniques of proving limit theorems for numerous statistics based on long memory processes. It also provides a guide to researchers about some of the inference problems under long memory.
Large Sample Inference For Long Memory Processes
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Author : Liudas Giraitis
language : en
Publisher:
Release Date : 2011
Large Sample Inference For Long Memory Processes written by Liudas Giraitis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Mathematical statistics categories.
Large Sample Inference For Long Memory Processes
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Author : Donatas Surgailis
language : en
Publisher: World Scientific Publishing Company
Release Date : 2012-04-27
Large Sample Inference For Long Memory Processes written by Donatas Surgailis and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-27 with Mathematics categories.
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./a
Long Memory Processes
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Author : Jan Beran
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-05-14
Long Memory Processes written by Jan Beran 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 2013-05-14 with Mathematics categories.
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.
Causal Inference In Econometrics
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Author : Van-Nam Huynh
language : en
Publisher: Springer
Release Date : 2015-12-28
Causal Inference In Econometrics written by Van-Nam Huynh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-28 with Technology & Engineering categories.
This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
Advances In Applied Econometrics
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Author : Subal C. Kumbhakar
language : en
Publisher: Springer Nature
Release Date : 2025-01-08
Advances In Applied Econometrics written by Subal C. Kumbhakar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-08 with Business & Economics categories.
This edited volume celebrates the profound legacy of Peter Schmidt, an eminent figure in econometric research. Originally featured as a Special Issue in Empirical Economics in 2023, this book gathers esteemed econometricians to honor Schmidt's influential work. His distinguished career encompassed pioneering contributions to various realms of econometrics, including time series and panel data econometrics, as well as stochastic frontier analysis. This Festschrift beautifully captures his synergy of theoretical innovation and empirical significance. Written by distinguished econometricians, the volume presents the state-of-the-art in econometrics, traversing Schmidt's diverse interests. It spotlights his impact on applied econometrics and features 25 contributions on topics such as panel data econometrics, stochastic frontier analysis and efficiency/productivity measurement, time series methods, general applied econometrics, copulas, nonparametric methods, andlimited dependent variable models. Readers will gain an overview of the state of econometrics through the lens of Schmidt's multifaceted expertise, exemplifying the enduring resonance of Schmidt's scholarly journey and his indelible impact on the field.
Time Series Analysis With Long Memory In View
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Author : Uwe Hassler
language : en
Publisher: John Wiley & Sons
Release Date : 2018-09-07
Time Series Analysis With Long Memory In View written by Uwe Hassler and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-07 with Mathematics categories.
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.
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
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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.
Directional Statistics For Innovative Applications
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Author : Ashis SenGupta
language : en
Publisher: Springer Nature
Release Date : 2022-06-15
Directional Statistics For Innovative Applications written by Ashis SenGupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-15 with Mathematics categories.
In commemoration of the bicentennial of the birth of the “lady who gave the rose diagram to us”, this special contributed book pays a statistical tribute to Florence Nightingale. This book presents recent phenomenal developments, both in rigorous theory as well as in emerging methods, for applications in directional statistics, in 25 chapters with contributions from 65 renowned researchers from 25 countries. With the advent of modern techniques in statistical paradigms and statistical machine learning, directional statistics has become an indispensable tool. Ranging from data on circles to that on the spheres, tori and cylinders, this book includes solutions to problems on exploratory data analysis, probability distributions on manifolds, maximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on.