Introduction to Empirical Processes and Semiparametric Inference - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Empirical Processes and Semiparametric Inference write by Michael R. Kosorok. This book was released on 2007-12-29. Introduction to Empirical Processes and Semiparametric Inference available in PDF, EPUB and Kindle. 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 with Applications to Statistics
Empirical Processes with Applications to Statistics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Empirical Processes with Applications to Statistics write by Galen R. Shorack. This book was released on 2009-01-01. Empirical Processes with Applications to Statistics available in PDF, EPUB and Kindle. Originally published in 1986, this valuable reference provides a detailed treatment of limit theorems and inequalities for empirical processes of real-valued random variables; applications of the theory to censored data, spacings, rank statistics, quantiles, and many functionals of empirical processes, including a treatment of bootstrap methods; and a summary of inequalities that are useful for proving limit theorems. At the end of the Errata section, the authors have supplied references to solutions for 11 of the 19 Open Questions provided in the book's original edition. Audience: researchers in statistical theory, probability theory, biostatistics, econometrics, and computer science.
Empirical Process Techniques for Dependent Data
Empirical Process Techniques for Dependent Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Empirical Process Techniques for Dependent Data write by Herold Dehling. This book was released on 2012-12-06. Empirical Process Techniques for Dependent Data available in PDF, EPUB and Kindle. 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,
Weak Convergence and Empirical Processes
Weak Convergence and Empirical Processes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Weak Convergence and Empirical Processes write by Aad van der vaart. This book was released on 2013-03-09. Weak Convergence and Empirical Processes available in PDF, EPUB and Kindle. This book explores weak convergence theory and empirical processes and their applications to many applications in statistics. Part one reviews stochastic convergence in its various forms. Part two offers the theory of empirical processes in a form accessible to statisticians and probabilists. Part three covers a range of topics demonstrating the applicability of the theory to key questions such as measures of goodness of fit and the bootstrap.
Weighted Empirical Processes in Dynamic Nonlinear Models
Weighted Empirical Processes in Dynamic Nonlinear Models - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Weighted Empirical Processes in Dynamic Nonlinear Models write by Hira L. Koul. This book was released on 2012-12-06. Weighted Empirical Processes in Dynamic Nonlinear Models available in PDF, EPUB and Kindle. This book presents a unified approach for obtaining the limiting distributions of minimum distance. It discusses classes of goodness-of-t tests for fitting an error distribution in some of these models and/or fitting a regression-autoregressive function without assuming the knowledge of the error distribution. The main tool is the asymptotic equi-continuity of certain basic weighted residual empirical processes in the uniform and L2 metrics.
