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Empirical Likelihood


Empirical Likelihood
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Empirical Likelihood


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



Empirical Likelihood Method In Survival Analysis


Empirical Likelihood Method In Survival Analysis
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Author : Mai Zhou
language : en
Publisher: CRC Press
Release Date : 2015-06-17

Empirical Likelihood Method In Survival Analysis written by Mai Zhou and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Mathematics categories.


Empirical Likelihood Method in Survival Analysis explains how to use the empirical likelihood method for right censored survival data. The author uses R for calculating empirical likelihood and includes many worked out examples with the associated R code. The datasets and code are available for download on his website and CRAN. The book focuses on all the standard survival analysis topics treated with empirical likelihood, including hazard functions, cumulative distribution functions, analysis of the Cox model, and computation of empirical likelihood for censored data. It also covers semi-parametric accelerated failure time models, the optimality of confidence regions derived from empirical likelihood or plug-in empirical likelihood ratio tests, and several empirical likelihood confidence band results. While survival analysis is a classic area of statistical study, the empirical likelihood methodology has only recently been developed. Until now, just one book was available on empirical likelihood and most statistical software did not include empirical likelihood procedures. Addressing this shortfall, this book provides the functions to calculate the empirical likelihood ratio in survival analysis as well as functions related to the empirical likelihood analysis of the Cox regression model and other hazard regression models.



Empirical Likelihood Methods In Biomedicine And Health


Empirical Likelihood Methods In Biomedicine And Health
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Author : Albert Vexler
language : en
Publisher: CRC Press
Release Date : 2018-09-03

Empirical Likelihood Methods In Biomedicine And Health written by Albert Vexler and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.


Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data. Provides a systematic overview of novel empirical likelihood techniques. Presents a good balance of theory, methods, and applications. Features detailed worked examples to illustrate the application of the methods. Includes R code for implementation. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.



Empirical Likelihood And Quantile Methods For Time Series


Empirical Likelihood And Quantile Methods For Time Series
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Author : Yan Liu
language : en
Publisher: Springer
Release Date : 2018-12-05

Empirical Likelihood And Quantile Methods For Time Series written by Yan Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-05 with Mathematics categories.


This book integrates the fundamentals of asymptotic theory of statistical inference for time series under nonstandard settings, e.g., infinite variance processes, not only from the point of view of efficiency but also from that of robustness and optimality by minimizing prediction error. This is the first book to consider the generalized empirical likelihood applied to time series models in frequency domain and also the estimation motivated by minimizing quantile prediction error without assumption of true model. It provides the reader with a new horizon for understanding the prediction problem that occurs in time series modeling and a contemporary approach of hypothesis testing by the generalized empirical likelihood method. Nonparametric aspects of the methods proposed in this book also satisfactorily address economic and financial problems without imposing redundantly strong restrictions on the model, which has been true until now. Dealing with infinite variance processes makes analysis of economic and financial data more accurate under the existing results from the demonstrative research. The scope of applications, however, is expected to apply to much broader academic fields. The methods are also sufficiently flexible in that they represent an advanced and unified development of prediction form including multiple-point extrapolation, interpolation, and other incomplete past forecastings. Consequently, they lead readers to a good combination of efficient and robust estimate and test, and discriminate pivotal quantities contained in realistic time series models.



Empirical Likelihood In Econometrics


Empirical Likelihood In Econometrics
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Author : Taisuke Otsu
language : en
Publisher:
Release Date : 2004

Empirical Likelihood In Econometrics written by Taisuke Otsu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.




The Extended Empirical Likelihood


The Extended Empirical Likelihood
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Author : Fan Wu
language : en
Publisher:
Release Date : 2015

The Extended Empirical Likelihood written by Fan Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.


The empirical likelihood method introduced by Owen (1988, 1990) is a powerful nonparametric method for statistical inference. It has been one of the most researched methods in statistics in the last twenty-five years and remains to be a very active area of research today. There is now a large body of literature on empirical likelihood method which covers its applications in many areas of statistics (Owen, 2001). One important problem affecting the empirical likelihood method is its poor accuracy, especially for small sample and/or high-dimension applications. The poor accuracy can be alleviated by using high-order empirical likelihood methods such as the Bartlett corrected empirical likelihood but it cannot be completely resolved by high-order asymptotic methods alone. Since the work of Tsao (2004), the impact of the convex hull constraint in the formulation of the empirical likelihood on the finite sample accuracy has been better understood, and methods have been developed to break this constraint in order to improve the accuracy.



Empirical Likelihood


Empirical Likelihood
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Author : Art B. Owen
language : en
Publisher: CRC Press
Release Date : 2001

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 with Estimation theory 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 also facilitates incorporating side information, and it simplifies accounting for censored, truncated, or biased sampling.One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies empirical likelihood to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Abundant figures offer visual reinforcement of the concepts and techniques.; Examples from a variety of disciplines and detailed descriptions of algorithms-also posted on a companion Web site at-illustrate the methods in practice. Exercises help readers to understand and apply the methods.The method of empirical likelihood is now attracting serious attention from researchers in econometrics and biostatistics, as well as from statisticians. This book is your opportunity to explore its foundations, its advantages, and its application to a myriad of practical problems.



A Pseudo Empirical Likelihood Approach To Nonignorable Nonresponse


A Pseudo Empirical Likelihood Approach To Nonignorable Nonresponse
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Author : Quan Hong
language : en
Publisher:
Release Date : 2004

A Pseudo Empirical Likelihood Approach To Nonignorable Nonresponse written by Quan Hong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.




Empirical Likelihood For Change Point Detection And Estimation In Time Series Models


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.



Some Aspects Of Empirical Likelihood


Some Aspects Of Empirical Likelihood
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Author : Xing Wang
language : en
Publisher:
Release Date : 2008

Some Aspects Of Empirical Likelihood written by Xing Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.