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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Autore principale: Mammen, Enno (Autore)
Natura: Article (Journal)
Lingua:inglese
Pubblicazione: 1991
In: The annals of statistics
Year: 1991, Volume: 19, Fascicolo: 2, Pages: 741-759
ISSN:2168-8966
DOI:10.1214/aos/1176348118
Accesso online: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
Testo
Note sull'autore:Enno Mammen
Descrizione
Riassunto: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.
Descrizione del documento:First available in Project Euclid: 12 April 2007
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Descrizione fisica:Online Resource
ISSN:2168-8966
DOI:10.1214/aos/1176348118