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Author : Robert David Murison
Publisher :
ISBN 13 :
Total Pages : 276 pages
Book Rating : 4.:/5 (222 download)
Download or read book Problems in Density Estimation for Independent and Dependent Data written by Robert David Murison and published by . This book was released on 1993 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Qi Li
Publisher : Princeton University Press
ISBN 13 : 1400841062
Total Pages : 769 pages
Book Rating : 4.4/5 (8 download)
Download or read book Nonparametric Econometrics written by Qi Li and published by Princeton University Press. This book was released on 2011-10-09 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.
Author : Jeffrey D. Hart
Publisher :
ISBN 13 :
Total Pages : 44 pages
Book Rating : 4.:/5 (13 download)
Download or read book Data-driven Bandwidth Choice for Density Estimation Based on Dependent Data written by Jeffrey D. Hart and published by . This book was released on 1988 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: The bandwidth selection problem in kernel density estimation is investigated in situations where the observed data are dependent. The classical leave-out technique is extended, and thereby a class of cross-validated bandwidths is defined. These bandwidths are shown to be asymptotically optimal under a strong mixing condition. The leave-one out, or ordinary, form of cross-validation remains asymptotically optimal under the dependence model considered. However, a simulation study shows that when the data are strongly enough correlated, the ordinary version of cross-validation can be improved upon in finite-sized samples.
Author : Bernard. W. Silverman
Publisher : Routledge
ISBN 13 : 1351456172
Total Pages : 176 pages
Book Rating : 4.3/5 (514 download)
Download or read book Density Estimation for Statistics and Data Analysis written by Bernard. W. Silverman and published by Routledge. This book was released on 2018-02-19 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there has been a surge of interest in density estimation in recent years, much of the published research has been concerned with purely technical matters with insufficient emphasis given to the technique's practical value. Furthermore, the subject has been rather inaccessible to the general statistician. The account presented in this book places emphasis on topics of methodological importance, in the hope that this will facilitate broader practical application of density estimation and also encourage research into relevant theoretical work. The book also provides an introduction to the subject for those with general interests in statistics. The important role of density estimation as a graphical technique is reflected by the inclusion of more than 50 graphs and figures throughout the text. Several contexts in which density estimation can be used are discussed, including the exploration and presentation of data, nonparametric discriminant analysis, cluster analysis, simulation and the bootstrap, bump hunting, projection pursuit, and the estimation of hazard rates and other quantities that depend on the density. This book includes general survey of methods available for density estimation. The Kernel method, both for univariate and multivariate data, is discussed in detail, with particular emphasis on ways of deciding how much to smooth and on computation aspects. Attention is also given to adaptive methods, which smooth to a greater degree in the tails of the distribution, and to methods based on the idea of penalized likelihood.
Author :
Publisher : Elsevier
ISBN 13 : 0323852017
Total Pages : 350 pages
Book Rating : 4.3/5 (238 download)
Download or read book Data Science: Theory and Applications written by and published by Elsevier. This book was released on 2021-02-12 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science: Theory and Applications, Volume 44 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of interesting topics, including Modeling extreme climatic events using the generalized extreme value distribution, Bayesian Methods in Data Science, Mathematical Modeling in Health Economic Evaluations, Data Science in Cancer Genomics, Blockchain Technology: Theory and Practice, Statistical outline of animal home ranges, an application of set estimation, Application of Data Handling Techniques to Predict Pavement Performance, Analysis of individual treatment effects for enhanced inferences in medicine, and more. Additional sections cover Nonparametric Data Science: Testing Hypotheses in Large Complex Data, From Urban Mobility Problems to Data Science Solutions, and Data Structures and Artificial Intelligence Methods. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Data Science: Theory and Applications
Author : Natalia Markovich
Publisher : John Wiley & Sons
ISBN 13 : 9780470723593
Total Pages : 336 pages
Book Rating : 4.7/5 (235 download)
Download or read book Nonparametric Analysis of Univariate Heavy-Tailed Data written by Natalia Markovich and published by John Wiley & Sons. This book was released on 2008-03-11 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution. The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function. Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.
Author : Peter Hall
Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.:/5 (221 download)
Download or read book On Bandwidth Choice for Density Estimation with Dependent Data written by Peter Hall and published by . This book was released on 1994 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Luc Devroye
Publisher : New York ; Toronto : Wiley
ISBN 13 :
Total Pages : 376 pages
Book Rating : 4.:/5 (319 download)
Download or read book Nonparametric Density Estimation written by Luc Devroye and published by New York ; Toronto : Wiley. This book was released on 1985-01-18 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a rigorous, systematic treatment of density estimates, their construction, use and analysis with full proofs. It develops L1 theory, rather than the classical L2, showing how L1 exposes fundamental properties of density estimates masked by L2.
Author : Alexander Meister
Publisher : Springer Science & Business Media
ISBN 13 : 3540875573
Total Pages : 211 pages
Book Rating : 4.5/5 (48 download)
Download or read book Deconvolution Problems in Nonparametric Statistics written by Alexander Meister and published by Springer Science & Business Media. This book was released on 2009-12-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deconvolution problems occur in many ?elds of nonparametric statistics, for example, density estimation based on contaminated data, nonparametric - gression with errors-in-variables, image and signal deblurring. During the last two decades, those topics have received more and more attention. As appli- tions of deconvolution procedures concern many real-life problems in eco- metrics, biometrics, medical statistics, image reconstruction, one can realize an increasing number of applied statisticians who are interested in nonpa- metric deconvolution methods; on the other hand, some deep results from Fourier analysis, functional analysis, and probability theory are required to understand the construction of deconvolution techniques and their properties so that deconvolution is also particularly challenging for mathematicians. Thegeneraldeconvolutionprobleminstatisticscanbedescribedasfollows: Our goal is estimating a function f while any empirical access is restricted to some quantity h = f?G = f(x?y)dG(y), (1. 1) that is, the convolution of f and some probability distribution G. Therefore, f can be estimated from some observations only indirectly. The strategy is ˆ estimating h ?rst; this means producing an empirical version h of h and, then, ˆ applying a deconvolution procedure to h to estimate f. In the mathematical context, we have to invert the convolution operator with G where some reg- ˆ ularization is required to guarantee that h is contained in the invertibility ˆ domain of the convolution operator. The estimator h has to be chosen with respect to the speci?c statistical experiment.
Author : Sam Efromovich
Publisher : CRC Press
ISBN 13 : 1351679848
Total Pages : 448 pages
Book Rating : 4.3/5 (516 download)
Download or read book Missing and Modified Data in Nonparametric Estimation written by Sam Efromovich and published by CRC Press. This book was released on 2018-03-12 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.
Author : P. Groeneboom
Publisher : Birkhäuser
ISBN 13 : 3034886217
Total Pages : 129 pages
Book Rating : 4.0/5 (348 download)
Download or read book Information Bounds and Nonparametric Maximum Likelihood Estimation written by P. Groeneboom and published by Birkhäuser. This book was released on 2012-12-06 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the lecture notes for a DMV course presented by the authors at Gunzburg, Germany, in September, 1990. In the course we sketched the theory of information bounds for non parametric and semiparametric models, and developed the theory of non parametric maximum likelihood estimation in several particular inverse problems: interval censoring and deconvolution models. Part I, based on Jon Wellner's lectures, gives a brief sketch of information lower bound theory: Hajek's convolution theorem and extensions, useful minimax bounds for parametric problems due to Ibragimov and Has'minskii, and a recent result characterizing differentiable functionals due to van der Vaart (1991). The differentiability theorem is illustrated with the examples of interval censoring and deconvolution (which are pursued from the estimation perspective in part II). The differentiability theorem gives a way of clearly distinguishing situations in which 1 2 the parameter of interest can be estimated at rate n / and situations in which this is not the case. However it says nothing about which rates to expect when the functional is not differentiable. Even the casual reader will notice that several models are introduced, but not pursued in any detail; many problems remain. Part II, based on Piet Groeneboom's lectures, focuses on non parametric maximum likelihood estimates (NPMLE's) for certain inverse problems. The first chapter deals with the interval censoring problem.
Author : Rand R. Wilcox
Publisher : Academic Press
ISBN 13 : 0123869838
Total Pages : 713 pages
Book Rating : 4.1/5 (238 download)
Download or read book Introduction to Robust Estimation and Hypothesis Testing written by Rand R. Wilcox and published by Academic Press. This book was released on 2012-01-12 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--
Author : Steven Paul Ellis
Publisher :
ISBN 13 :
Total Pages : 482 pages
Book Rating : 4.:/5 (29 download)
Download or read book Density Estimation for Point Process Data written by Steven Paul Ellis and published by . This book was released on 1981 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jianqing Fan
Publisher : Springer Science & Business Media
ISBN 13 : 0387693955
Total Pages : 565 pages
Book Rating : 4.3/5 (876 download)
Download or read book Nonlinear Time Series written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2008-09-11 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.
Author : Jesper Møller
Publisher : Springer Science & Business Media
ISBN 13 : 0387218114
Total Pages : 217 pages
Book Rating : 4.3/5 (872 download)
Download or read book Spatial Statistics and Computational Methods written by Jesper Møller and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume shows how sophisticated spatial statistical and computational methods apply to a range of problems of increasing importance for applications in science and technology. It introduces topics of current interest in spatial and computational statistics, which should be accessible to postgraduate students as well as to experienced statistical researchers.
Author : Giovanni C. Porzio
Publisher : Firenze University Press
ISBN 13 : 8855183400
Total Pages : 455 pages
Book Rating : 4.8/5 (551 download)
Download or read book CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS written by Giovanni C. Porzio and published by Firenze University Press. This book was released on with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book collects the short papers presented at the 13th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS). The meeting has been organized by the Department of Statistics, Computer Science and Applications of the University of Florence, under the auspices of the Italian Statistical Society and the International Federation of Classification Societies (IFCS). CLADAG is a member of the IFCS, a federation of national, regional, and linguistically-based classification societies. It is a non-profit, non-political scientific organization, whose aims are to further classification research.
Author : Ken-ichi Yoshihara
Publisher :
ISBN 13 :
Total Pages : 356 pages
Book Rating : 4.3/5 (91 download)
Download or read book Weakly Dependent Stochastic Sequences and Their Applications: Curve estimation based on weakly dependent data written by Ken-ichi Yoshihara and published by . This book was released on 1992 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:
