Smoothing parameter selection in two frameworks for penalized splines

Veröffentlichungen: Beitrag in FachzeitschriftArtikelPeer Reviewed

Abstract

There are two popular smoothing parameter selection methods for spline smoothing. First, smoothing parameters can be estimated by minimizing criteria that approximate the average mean-squared error of the regression function estimator. Second, the maximum likelihood paradigm can be employed, under the assumption that the regression function is a realization of some stochastic process. The asymptotic properties of both smoothing parameter estimators for penalized splines are studied and compared. A simulation study and a real data example illustrate the theoretical findings.
OriginalspracheEnglisch
Seiten (von - bis)725-741
Seitenumfang17
FachzeitschriftJournal of the Royal Statistical Society B: Statistical Methodology
Jahrgang75
Ausgabenummer4
Frühes Online-DatumMärz 2013
PublikationsstatusVeröffentlicht - Sep. 2013
Extern publiziertJa

ÖFOS 2012

  • 101018 Statistik

Schlagwörter

  • ISOR

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