Empirical Likelihood In Long Memory Time Series Models
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Empirical Likelihood In Long Memory Time Series Models
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Author : Chun-Yip Yau
language : en
Publisher:
Release Date : 2006
Empirical Likelihood In Long Memory Time Series Models written by Chun-Yip Yau and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Time-series analysis categories.
Empirical Likelihood For Change Point Detection And Estimation In Time Series Models
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Author : Ramadha D Piyadi Gamage
language : en
Publisher:
Release Date : 2017
Empirical Likelihood For Change Point Detection And Estimation In Time Series Models written by Ramadha D Piyadi Gamage and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Change-point problems categories.
Empirical Likelihood (EL) method introduced by Owen (1988) is a widely used nonparametric tool for constructing confidence regions due to its appealing asymptotic distribution of the likelihood-ratio-type statistic which is same as the one under the parametric settings. However, the EL method was introduced to be used for independent data, hence it becomes difficult to apply it to dependent data such as time series data. Owen (2001) suggested using the conditional likelihood to remove the dependence structure and generate the estimating equations. Monti (1997) developed the idea of extending the EL method to short-memory time series models using the Whittle's (1953) estimation method to obtain an M-estimator of the periodogram ordinates of a time series which are asymptotically independent. This reduces a dependent data problem into an independent data problem. Nordman and Lahiri (2006) also formulated a frequency domain empirical likelihood (FDEL) using spectral estimating equations which can be used for short- and long- range dependent data. FDEL applies a data transformation which weakens the dependence structure of the data hence, allowing to use the EL method for the transformed data which is considered to be asymptotically independent. Unfortunately, there is a good chance that the solution to the profile empirical likelihood function computation which involves constrained maximization does not exist which raises some computational issues as mentioned by Chen et al. (2008). To overcome this difficulty, Chen et al. (2008) proposed an adjusted empirical likelihood (AEL) ratio function by adding a pseudo term to guarantee the zero to be an interior point of the convex hull, therefore, the required numerical maximization is guaranteed to have a solution always. This dissertation focuses on developing novel nonparametric tests based on the empirical likelihood to estimate and detect changes in parameters of various times series models. First part is focused on the AEL for short-memory time series models such as autoregression (AR), moving average (MA), autoregressive moving average (ARMA), etc. I incorporated Monti's (1997) approach along with Nordman and Lahiri's (2006) formulation, to propose an AEL for short-memory dependence data. In the second part, an AEL-type statistic has been established for long-memory time series models suggested by Yau (2012). The third part of the dissertation focuses on the detection of changes in structures of time series models based on the EL method. Real data sets are used in each section to illustrate the performance of the proposed methods.
Long Memory Time Series
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Author : Wilfredo Palma
language : en
Publisher: John Wiley & Sons
Release Date : 2007-04-27
Long Memory Time Series written by Wilfredo Palma 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 2007-04-27 with Mathematics categories.
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.
Long Range Dependent Processes Theory And Applications
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Author : Ming Li
language : en
Publisher: Frontiers Media SA
Release Date : 2022-12-05
Long Range Dependent Processes Theory And Applications written by Ming Li and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-05 with Science categories.
Empirical Likelihood
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Author : Art B. Owen
language : en
Publisher: CRC Press
Release Date : 2001-05-18
Empirical Likelihood written by Art B. Owen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-05-18 with Mathematics categories.
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It al
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.
Bartlett Correction Of Empirical Likelihood For Non Gaussian Short Memory Time Series
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Author : Kun Chen
language : en
Publisher:
Release Date : 2016
Bartlett Correction Of Empirical Likelihood For Non Gaussian Short Memory Time Series written by Kun Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Bartlett correction, which improves the coverage accuracies of confidence regions, is one of the desirable features of empirical likelihood. For empirical likelihood with dependent data, previous studies on the Bartlett correction are mainly concerned with Gaussian processes. By establishing the validity of Edgeworth expansion for the signed root empirical log-likelihood ratio statistics, we show that the Bartlett correction is applicable to empirical likelihood for short-memory time series with possibly non-Gaussian innovations. The Bartlett correction is established under the assumptions that the variance of the innovation is known and the mean of the underlying process is zero for a single parameter model. In particular, the order of the coverage errors of Bartlett-corrected confidence regions can be reduced from O(n-1) to O(n-2).
Introduction To Statistical Time Series
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Author : Wayne A. Fuller
language : en
Publisher: John Wiley & Sons
Release Date : 1995-12-29
Introduction To Statistical Time Series written by Wayne A. Fuller 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 1995-12-29 with Mathematics categories.
The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material,especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.
Time Series With Long Memory
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Author : Peter M. Robinson
language : en
Publisher: Advanced Texts in Econometrics
Release Date : 2003
Time Series With Long Memory written by Peter M. Robinson and has been published by Advanced Texts in Econometrics this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.
Long memory time series are characterized by a strong dependence between distant events.