Empirical Process Techniques For Dependent Data

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Empirical Process Techniques for Dependent Data

Author : Herold Dehling
Publisher : Springer Science & Business Media
ISBN 13 : 1461200997
Total Pages : 378 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Empirical Process Techniques for Dependent Data by : Herold Dehling

Download or read book Empirical Process Techniques for Dependent Data written by Herold Dehling and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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,

Empirical Process Techniques for Dependent Data

Author : Herold Dehling
Publisher : Birkhauser
ISBN 13 : 9783764342012
Total Pages : 381 pages
Book Rating : 4.3/5 (42 download)

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Book Synopsis Empirical Process Techniques for Dependent Data by : Herold Dehling

Download or read book Empirical Process Techniques for Dependent Data written by Herold Dehling and published by Birkhauser. This book was released on 2002-01-01 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Empirical Processes and Semiparametric Inference

Author : Michael R. Kosorok
Publisher : Springer Science & Business Media
ISBN 13 : 0387749780
Total Pages : 482 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Introduction to Empirical Processes and Semiparametric Inference by : Michael R. Kosorok

Download or read book Introduction to Empirical Processes and Semiparametric Inference written by Michael R. Kosorok and published by Springer Science & Business Media. This book was released on 2007-12-29 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kosorok’s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. This is an authoritative text that covers all the bases, and also a friendly and gradual introduction to the area. The book can be used as research reference and textbook.

Empirical Processes

Author : David Pollard
Publisher : IMS
ISBN 13 : 9780940600164
Total Pages : 100 pages
Book Rating : 4.6/5 (1 download)

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Book Synopsis Empirical Processes by : David Pollard

Download or read book Empirical Processes written by David Pollard and published by IMS. This book was released on 1990 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

High-Dimensional Probability

Author : Roman Vershynin
Publisher : Cambridge University Press
ISBN 13 : 1108415199
Total Pages : 299 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis High-Dimensional Probability by : Roman Vershynin

Download or read book High-Dimensional Probability written by Roman Vershynin and published by Cambridge University Press. This book was released on 2018-09-27 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems

Author : Vladimir Koltchinskii
Publisher : Springer
ISBN 13 : 3642221475
Total Pages : 254 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems by : Vladimir Koltchinskii

Download or read book Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems written by Vladimir Koltchinskii and published by Springer. This book was released on 2011-07-29 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of these lecture notes is to provide an introduction to the general theory of empirical risk minimization with an emphasis on excess risk bounds and oracle inequalities in penalized problems. In recent years, there have been new developments in this area motivated by the study of new classes of methods in machine learning such as large margin classification methods (boosting, kernel machines). The main probabilistic tools involved in the analysis of these problems are concentration and deviation inequalities by Talagrand along with other methods of empirical processes theory (symmetrization inequalities, contraction inequality for Rademacher sums, entropy and generic chaining bounds). Sparse recovery based on l_1-type penalization and low rank matrix recovery based on the nuclear norm penalization are other active areas of research, where the main problems can be stated in the framework of penalized empirical risk minimization, and concentration inequalities and empirical processes tools have proved to be very useful.

Weak Convergence of Stochastic Processes

Author : Vidyadhar S. Mandrekar
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110475456
Total Pages : 148 pages
Book Rating : 4.1/5 (14 download)

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Book Synopsis Weak Convergence of Stochastic Processes by : Vidyadhar S. Mandrekar

Download or read book Weak Convergence of Stochastic Processes written by Vidyadhar S. Mandrekar and published by Walter de Gruyter GmbH & Co KG. This book was released on 2016-09-26 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion. Contents: Weak convergence of stochastic processes Weak convergence in metric spaces Weak convergence on C[0, 1] and D[0,∞) Central limit theorem for semi-martingales and applications Central limit theorems for dependent random variables Empirical process Bibliography

Empirical Likelihood

Author : Art B. Owen
Publisher : CRC Press
ISBN 13 : 1420036157
Total Pages : 322 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Empirical Likelihood by : Art B. Owen

Download or read book Empirical Likelihood written by Art B. Owen and published by CRC Press. This book was released on 2001-05-18 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Functional Gaussian Approximation for Dependent Structures

Author : Florence Merlevède
Publisher : Oxford University Press
ISBN 13 : 0192561863
Total Pages : 496 pages
Book Rating : 4.1/5 (925 download)

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Book Synopsis Functional Gaussian Approximation for Dependent Structures by : Florence Merlevède

Download or read book Functional Gaussian Approximation for Dependent Structures written by Florence Merlevède and published by Oxford University Press. This book was released on 2019-02-14 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Functional Gaussian Approximation for Dependent Structures develops and analyses mathematical models for phenomena that evolve in time and influence each another. It provides a better understanding of the structure and asymptotic behaviour of stochastic processes. Two approaches are taken. Firstly, the authors present tools for dealing with the dependent structures used to obtain normal approximations. Secondly, they apply normal approximations to various examples. The main tools consist of inequalities for dependent sequences of random variables, leading to limit theorems, including the functional central limit theorem and functional moderate deviation principle. The results point out large classes of dependent random variables which satisfy invariance principles, making possible the statistical study of data coming from stochastic processes both with short and long memory. The dependence structures considered throughout the book include the traditional mixing structures, martingale-like structures, and weakly negatively dependent structures, which link the notion of mixing to the notions of association and negative dependence. Several applications are carefully selected to exhibit the importance of the theoretical results. They include random walks in random scenery and determinantal processes. In addition, due to their importance in analysing new data in economics, linear processes with dependent innovations will also be considered and analysed.

Uniform Central Limit Theorems

Author : R. M. Dudley
Publisher : Cambridge University Press
ISBN 13 : 0521461022
Total Pages : 452 pages
Book Rating : 4.5/5 (214 download)

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Book Synopsis Uniform Central Limit Theorems by : R. M. Dudley

Download or read book Uniform Central Limit Theorems written by R. M. Dudley and published by Cambridge University Press. This book was released on 1999-07-28 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This treatise by an acknowledged expert includes several topics not found in any previous book.

Statistical Inference for Discrete Time Stochastic Processes

Author : M. B. Rajarshi
Publisher : Springer Science & Business Media
ISBN 13 : 8132207637
Total Pages : 121 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Statistical Inference for Discrete Time Stochastic Processes by : M. B. Rajarshi

Download or read book Statistical Inference for Discrete Time Stochastic Processes written by M. B. Rajarshi and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is an overview of statistical inference in stationary, discrete time stochastic processes. Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis have been reviewed. The first chapter gives a background of results on martingales and strong mixing sequences, which enable us to generate various classes of CAN estimators in the case of dependent observations. Topics discussed include inference in Markov chains and extension of Markov chains such as Raftery's Mixture Transition Density model and Hidden Markov chains and extensions of ARMA models with a Binomial, Poisson, Geometric, Exponential, Gamma, Weibull, Lognormal, Inverse Gaussian and Cauchy as stationary distributions. It further discusses applications of semi-parametric methods of estimation such as conditional least squares and estimating functions in stochastic models. Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel based estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures for dependent sequences such as Markov chains, Markov sequences, linear auto-regressive moving average sequences, block based bootstrap for stationary sequences and other block based procedures are also discussed in some detail. This work can be useful for researchers interested in knowing developments in inference in discrete time stochastic processes. It can be used as a material for advanced level research students.

Microeconometrics

Author : A. Colin Cameron
Publisher : Cambridge University Press
ISBN 13 : 1139444867
Total Pages : 1058 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Microeconometrics by : A. Colin Cameron

Download or read book Microeconometrics written by A. Colin Cameron and published by Cambridge University Press. This book was released on 2005-05-09 with total page 1058 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.

Contemporary Developments in Statistical Theory

Author : Soumendra Lahiri
Publisher : Springer Science & Business Media
ISBN 13 : 3319026518
Total Pages : 395 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Contemporary Developments in Statistical Theory by : Soumendra Lahiri

Download or read book Contemporary Developments in Statistical Theory written by Soumendra Lahiri and published by Springer Science & Business Media. This book was released on 2013-12-02 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume highlights Prof. Hira Koul’s achievements in many areas of Statistics, including Asymptotic theory of statistical inference, Robustness, Weighted empirical processes and their applications, Survival Analysis, Nonlinear time series and Econometrics, among others. Chapters are all original papers that explore the frontiers of these areas and will assist researchers and graduate students working in Statistics, Econometrics and related areas. Prof. Hira Koul was the first Ph.D. student of Prof. Peter Bickel. His distinguished career in Statistics includes the receipt of many prestigious awards, including the Senior Humbolt award (1995), and dedicated service to the profession through editorial work for journals and through leadership roles in professional societies, notably as the past president of the International Indian Statistical Association. Prof. Hira Koul has graduated close to 30 Ph.D. students, and made several seminal contributions in about 125 innovative research papers. The long list of his distinguished collaborators is represented by the contributors to this volume.

Weak Dependence: With Examples and Applications

Author : Jérome Dedecker
Publisher : Springer Science & Business Media
ISBN 13 : 038769952X
Total Pages : 326 pages
Book Rating : 4.3/5 (876 download)

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Book Synopsis Weak Dependence: With Examples and Applications by : Jérome Dedecker

Download or read book Weak Dependence: With Examples and Applications written by Jérome Dedecker and published by Springer Science & Business Media. This book was released on 2007-07-29 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops Doukhan/Louhichi's 1999 idea to measure asymptotic independence of a random process. The authors, who helped develop this theory, propose examples of models fitting such conditions: stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Applications are still needed to develop a method of analysis for nonlinear times series, and this book provides a strong basis for additional studies.

Contemporaneous Event Studies in Corporate Finance

Author : Jau-Lian Jeng
Publisher : Springer Nature
ISBN 13 : 3030538095
Total Pages : 239 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Contemporaneous Event Studies in Corporate Finance by : Jau-Lian Jeng

Download or read book Contemporaneous Event Studies in Corporate Finance written by Jau-Lian Jeng and published by Springer Nature. This book was released on 2020-11-03 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a comprehensive overview of event study methodology in the field of corporate finance, this book discusses how traditional methods verify the significance and insignificance of events in statistical sampling, and emphasize possible deviation from the statistics of interest. However, the author illustrates the flaws of conventional methodology and proposes alternative methods which can be used for a more robust study of estimating normal and abnormal returns. Traditional methods fail to recognize that the importance of an event will also influence the frequency of the occurrence of the event, and consequently they produce subjective sampling results. This book highlights contemporaneous recursive methods which can be used to track down normal returns and avoid arbitrary determination for the estimation and event period. In addition, the author offers an alternative monitoring scheme to identify the events of concern. Addressing a need for more objective sampling methods in corporate finance event studies, this timely book will appeal to students and academics researching financial econometrics and time series analysis, corporate finance and capital markets.

Large Sample Techniques for Statistics

Author : Jiming Jiang
Publisher : Springer Science & Business Media
ISBN 13 : 144196827X
Total Pages : 612 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Large Sample Techniques for Statistics by : Jiming Jiang

Download or read book Large Sample Techniques for Statistics written by Jiming Jiang and published by Springer Science & Business Media. This book was released on 2010-06-30 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a way, the world is made up of approximations, and surely there is no exception in the world of statistics. In fact, approximations, especially large sample approximations, are very important parts of both theoretical and - plied statistics.TheGaussiandistribution,alsoknownasthe normaldistri- tion,is merelyonesuchexample,dueto thewell-knowncentrallimittheorem. Large-sample techniques provide solutions to many practical problems; they simplify our solutions to di?cult, sometimes intractable problems; they j- tify our solutions; and they guide us to directions of improvements. On the other hand, just because large-sample approximations are used everywhere, and every day, it does not guarantee that they are used properly, and, when the techniques are misused, there may be serious consequences. 2 Example 1 (Asymptotic? distribution). Likelihood ratio test (LRT) is one of the fundamental techniques in statistics. It is well known that, in the 2 “standard” situation, the asymptotic null distribution of the LRT is?,with the degreesoffreedomequaltothe di?erencebetweenthedimensions,de?ned as the numbers of free parameters, of the two nested models being compared (e.g., Rice 1995, pp. 310). This might lead to a wrong impression that the 2 asymptotic (null) distribution of the LRT is always? . A similar mistake 2 might take place when dealing with Pearson’s? -test—the asymptotic distri- 2 2 bution of Pearson’s? -test is not always? (e.g., Moore 1978).

Econometric Analysis of Cross Section and Panel Data, second edition

Author : Jeffrey M. Wooldridge
Publisher : MIT Press
ISBN 13 : 0262232588
Total Pages : 1095 pages
Book Rating : 4.2/5 (622 download)

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Book Synopsis Econometric Analysis of Cross Section and Panel Data, second edition by : Jeffrey M. Wooldridge

Download or read book Econometric Analysis of Cross Section and Panel Data, second edition written by Jeffrey M. Wooldridge and published by MIT Press. This book was released on 2010-10-01 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.