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Nonparametric Regression and Spline Smoothing
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Book Description
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.
Table of Contents
What is a good estimator?; series estimators; kernel estimators; smoothing splines; least-square splines.
Author(s)
Biography
Randall L. Eubank