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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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
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Verfasserangaben:Enno Mammen

MARC

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520 |a 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. 
650 4 |a Nonparametric regression 
650 4 |a estimation of the shape of a function 
650 4 |a isotonic and concave regression 
650 4 |a simple qualitative curve characteristics 
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