Results 261 to 270 of about 205,425 (288)

How to Select the Smoothing Parameter?

1989
From the results given in the previous sections it appeared that the bandwidth h played a dominant role in the behaviour of kernel estimates for regression, density or hazard function estimation.
Lázió Györfi, Wolfgang Härdle, Pascal Sarda, Philippe Vieu   +3 more
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Nonparametric regression for functional data: Automatic smoothing parameter selection

Journal of Statistical Planning and Inference, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rachdi, Mustapha, Vieu, Philippe
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Smoothing Parameter Selection in Image Restoration

1991
We consider the problem of the automatic selection of the smoothing parameter in image restoration using the method of regularisation. We consider two new smoothing parameter selectors based on the estimation cross-validation function and compare their performance with some others proposed in the literature and also with some optimal methods.
K. P.-S. Chan, J. W. Kay
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A note on smoothing parameter selection for penalized spline smoothing

Journal of Statistical Planning and Inference, 2005
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REGRESSION SMOOTHING PARAMETER SELECTION USING CROSS RESIDUALS SUM

Communications in Statistics - Theory and Methods, 2002
ABSTRACT In this paper the well-known regression smoothing parameter selection problem is revisited. Rice (Rice, J. Bandwidth Choice for Nonparametric Regression. The Annals of Statistics 1984, 12, 1215–1230.) and Hardle et al. (Hardle, W.; Hall, P.; Marron, J.S. How Far Are Automatically Chosen Regression Parameters from Their Optimum?
Tae Yoon Kim, Cheolyong Park
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Adaptive testing using data-driven method selecting smoothing parameters

Economics Letters, 2022
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Gradient-based smoothing parameter selection for nonparametric regression estimation

Journal of Econometrics, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Henderson, Daniel J., Li, Qi, Parmeter, Christopher F., Yao, Shuang   +3 more
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Some characteristics on the selection of spline smoothing parameter

Communications in Statistics - Theory and Methods, 2017
ABSTRACTThe smoothing spline method is used to fit a curve to a noisy data set, where selection of the smoothing parameter is essential. An adaptive Cp criterion (Chen and Huang 2011) based on the Stein’s unbiased risk estimate has been proposed to select the smoothing parameter, which not only considers the usual effective degrees of freedom but also ...
Chun-Shu Chen, Yi-Tsz Huang
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Automatic smoothing parameter selection in non‐parametric models for longitudinal data

Applied Stochastic Models and Data Analysis, 1997
An automatic smoothing parameter selection procedure, known as BRUTO, that uses a modified version of the generalized cross-validation (GCV) criterion by exploiting the advantages of the backfitting algorithm is not directly applicable to longitudinal data since the use of GCV leads to undersmoothing or oversmoothing depending on the nature of the ...
Berhane, Kiros, Rao, J. Sunil
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ASYMPTOTIC STABILITY OF THE OSCV SMOOTHING PARAMETER SELECTION

Communications in Statistics - Theory and Methods, 2001
The smoothing parameter selection by the one-sided cross-validation (OSCV) method is completely automatic in that it does not require extra parameters estimation. Also it reduces the variability comparable to that of plug-in rules. In this paper we derive analytically the asymptotic variance of the smoothing parameter selected by OSCV.
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