Nonparametric Regression and Spline Smoothing

Presents an account of popular approaches to nonparametric regression smoothing. This book discusses boundary corrections for trigonometric series estimators; asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; and practical aspects, problems and methods for confidence intervals and bands.

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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.