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A Class of Non-parametric Estimates of a Smooth Regression Function

A Class of Non-parametric Estimates of a Smooth Regression Function
Author: R. M. Royall
Publisher:
Total Pages: 164
Release: 1966
Genre: Mathematical statistics
ISBN:

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The purpose of the paper is to develop methods for estimating regression functions (i.e., conditional expectations) when nothing is known or assumed about their underlying functional form. The approach is 'non-parametric' in the sense that the regression function itself, rather than a set of numerical parameters, is estimated. The methods given make use of certain rank order statistics and thereby avoid problems of scaling which are troublesome when less sophisticated non-parametric methods are used. The large sample performance of the proposed regression estimators is studied in detail and methods for obtaining high orders of asymptotic efficiency are given. The asymptotic (normal) distribution of the estimates is obtained and the related problem of prediction is discussed. (Author).


Nonparametric Regression and Spline Smoothing, Second Edition

Nonparametric Regression and Spline Smoothing, Second Edition
Author: Randall L. Eubank
Publisher: CRC Press
Total Pages: 368
Release: 1999-02-09
Genre: Mathematics
ISBN: 9780824793371

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Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.


Nonparametric Regression and Spline Smoothing

Nonparametric Regression and Spline Smoothing
Author: Randall L. Eubank
Publisher: CRC Press
Total Pages: 359
Release: 1999-02-09
Genre: Mathematics
ISBN: 1482273144

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Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for co


Nonparametric Functional Estimation and Related Topics

Nonparametric Functional Estimation and Related Topics
Author: George Roussas
Publisher: Springer Science & Business Media
Total Pages: 732
Release: 1991-04-30
Genre: Mathematics
ISBN: 9780792312260

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About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.


Kernel Smoothing

Kernel Smoothing
Author: M.P. Wand
Publisher: CRC Press
Total Pages: 227
Release: 1994-12-01
Genre: Mathematics
ISBN: 1482216124

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Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function. This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilita