A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
Annals of Statistics
Laurie Davies and Arne Kovac have written a nice and very stimulating paper on nonparametric regression. They propose a novel approach to curve estimation, combining the traditional notion of estimation error (measured by supremum norm) and the complexity of the fitted function (measured by its modality). My comments are formulated in terms of a "true" underlying regression function f.doi:10.1214/aos/996986501 fatcat:tyriac5dprdgbouag7bh7k2bdi