Smoothing noisy data for irregular regions using penalized bivariate splines on triangulations

Lan Zhou () and Huijun Pan ()

Computational Statistics, 2014, vol. 29, issue 1, 263-281

Abstract: The penalized spline method has been widely used for estimating univariate smooth functions based on noisy data. This paper studies its extension to the two-dimensional case. To accommodate the need of handling data distributed on irregular regions, we consider bivariate splines defined on triangulations. Penalty functions based on the second-order derivatives are employed to regularize the spline fit and generalized cross-validation is used to select the penalty parameters. A simulation study shows that the penalized bivariate spline method is competitive to some well-established two-dimensional smoothers. The method is also illustrated using a real dataset on Texas temperature. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Bivariate smoothing; Generalized cross-validation; Nonparametric function estimation; Roughness penalty; P-splines (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:29:y:2014:i:1:p:263-281

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DOI: 10.1007/s00180-013-0448-z

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