Resistant selection of the smoothing parameter for smoothing splines

Authors:
Eva Cantoni;Elvezio Ronchetti
Affiliations:
Department of Econometrics, University of Geneva, CH-1211 Geneva 4, Switzerland;Department of Econometrics, University of Geneva, CH-1211 Geneva 4, Switzerland
Venue:
Statistics and Computing
Year:
2001

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Abstract

Robust automatic selection techniques for the smoothing parameter of a smoothing spline are introduced. They are based on a robust predictive error criterion and can be viewed as robust versions of Cp and cross-validation. They lead to smoothing splines which are stable and reliable in terms of mean squared error over a large spectrum of model distributions.