Results 271 to 280 of about 448,585 (316)

Exact risk approaches to smoothing parameter selection

Journal of Nonparametric Statistics, 1997
The past decade has seen the development of a large number of second-generational smoothing parameter selectors as a response to the high degree of variability of cross-validatory methods. However, most of these rules rely on asymptotic approximations which make them subject to adverse performance when the approximations are poor.
M P Wand
exaly   +3 more sources

Nonlinearly Smoothed EM Density Estimation With Automated Smoothing Parameter Selection for Nonparametric Deconvolution Problems

Journal of the American Statistical Association, 1997
Abstract We study a nonparametric deconvolution density estimation problem. The estimator is obtained by an EM algorithm for a smoothed maximum likelihood estimation problem, which has a unique continuous solution. We present an implementation of the procedure incorporating a data-driven discrepancy principle for selecting the smoothing parameter ...
P P B Eggermont, V N Lariccia
exaly   +5 more sources

Smoothing parameter selection for smooth distribution functions

Journal of Statistical Planning and Inference, 1993
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
P. Sarda
openaire   +2 more sources

Automatic smoothing parameter selection in GAMLSS with an application to centile estimation

Statistical Methods in Medical Research, 2013
A method for automatic selection of the smoothing parameters in a generalised additive model for location, scale and shape (GAMLSS) model is introduced. The method uses a P-spline representation of the smoothing terms to express them as random effect terms with an internal (or local) maximum likelihood estimation on the predictor scale of each ...
Robert A, Rigby, Dimitrios M, Stasinopoulos   +1 more
openaire   +3 more sources

Smoothing parameter selection in hazard estimation

Statistics & Probability Letters, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sarda, P., Vieu, P.
openaire   +3 more sources

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
openaire   +5 more sources

Smoothing parameter selection for nonparametric regression using smoothing spline

, 2013
In this paper, the smoothing parameter selection problem has been examined in respect to a smoothing spline implementation in predicting nonparametric regression models. For this purpose, a simulation study has been performed by using a program written in MATLAB.
Aydin, Dursun, Memmedli, Memmedaga, Omay, Rabia Ece   +2 more
openaire   +3 more sources

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
openaire   +2 more sources

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.
Seongbaek Yi
openaire   +2 more sources

An innovative procedure for smoothing parameter selection

, 2012
Smoothing with penalized splines calls for an automatic method to select the size of the penalty parameter λ. We propose a not well known smoothing parameter selection procedure: the L-curve method. AIC and (generalized) cross validation represent the most common choices in this kind of problems even if they indicate light smoothing when the data ...
Frasso, Gianluca, Eilers, Paul H.C.
openaire   +2 more sources