Asymptotics and smoothing parameter selection for penalized spline regression with various loss functions

Penalized splines are used in various types of regression analyses, including non-parametric quantile, robust and the usual mean regression. In this paper, we focus on the penalized spline estimator with general convex loss functions. By specifying the loss function, we can obtain the mean estimator, quantile estimator and robust estimator. We will first study the asymptotic properties of penalized splines. Specifically, we will show the asymptotic bias and variance as well as the asymptotic normality of the estimator. Next, we will discuss smoothing parameter selection for the minimization of... Mehr ...

Verfasser: Yoshida, Takuma
Dokumenttyp: Artikel
Reihe/Periodikum: Statistica Neerlandica
Verlag/Hrsg.: Oxford, Blackwell
Sprache: Englisch
ISSN: 0039-0402
Weitere Identifikatoren: doi: 10.1111/stan.12088
Permalink: https://search.fid-benelux.de/Record/olc-benelux-1984451227
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Datenquelle: Online Contents Benelux; Originalkatalog
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Link(s) : http://dx.doi.org/10.1111/stan.12088
http://dx.doi.org/10.1111/stan.12088