Smoothing Techniques for Curve Estimation

Inhaltsverzeichnis

• Nonparametric curve estimation.
• A tree-structured approach to nonparametric multiple regression.
• Kernel estimation of regression functions.
• Total least squares.
• Some theoretical results on Tukey’s 3R smoother.
• Bias- and efficiency-robustness of general M-estimators for regression with random carriers.
• Approximate conditional-mean type smoothers and interpolators.
• Optimal convergence properties of kernel estimates of derivatives of a density function.
• Density quantile estimation approach to statistical data modelling.
• Global measures of deviation for kernel and nearest neighbor density estimates.
• Some comments on the asymptotic behavior of robust smoothers.
• Cross-validation techniques for smoothing spline functions in one or two dimensions.
• Convergence rates of „thin plate“ smoothing splines wihen the data are noisy.