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 | Statistics
