Flexible, boundary adapted, nonparametric methods for the estimation of univariate piecewise-smooth functions
Academic Article
Publication Date:
2020
abstract:
We present and compare some nonparametric estimation methods (wavelet and/or spline-based) designed to recover a one-dimensional piecewise-smooth regression function in both a fixed equidistant or not equidistant design regression model and a random design model.
Iris type:
01.01 Articolo in rivista
Keywords:
Wavelets; boundary corrections; nonparametric regression; smoothing splines; thresholding; model selection; backfitting
List of contributors:
Amato, Umberto; DE FEIS, Italia
Published in: