Nonparametric regression under qualitative smoothness assumptions

We propose a new nonparametric regression estimate. In contrast to the traditional approach of considering regression functions whose mmmth derivatives lie in a ball in the L∞L∞L_\infty or L2L2L_2 norm, we consider the class of functions whose (m−1)(m−1)(m - 1)st derivative consists of at most kkk m...

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Bibliographische Detailangaben
1. Verfasser: Mammen, Enno (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 1991
In: The annals of statistics
Year: 1991, Jahrgang: 19, Heft: 2, Pages: 741-759
ISSN:2168-8966
DOI:10.1214/aos/1176348118
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1214/aos/1176348118
Verlag, Volltext: https://projecteuclid.org/euclid.aos/1176348118
Verlag, Volltext: https://projecteuclid.org/download/pdf_1/euclid.aos/1176348118
Volltext
Verfasserangaben:Enno Mammen
Beschreibung
Zusammenfassung:We propose a new nonparametric regression estimate. In contrast to the traditional approach of considering regression functions whose mmmth derivatives lie in a ball in the L∞L∞L_\infty or L2L2L_2 norm, we consider the class of functions whose (m−1)(m−1)(m - 1)st derivative consists of at most kkk monotone pieces. For many applications this class seems more natural than the classical ones. The least squares estimator of this class is studied. It is shown that the speed of convergence is as fast as in the classical case.
Beschreibung:First available in Project Euclid: 12 April 2007
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Beschreibung:Online Resource
ISSN:2168-8966
DOI:10.1214/aos/1176348118