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CSDA
2010
119views more  CSDA 2010»
13 years 4 months ago
Fast robust estimation of prediction error based on resampling
Robust estimators of the prediction error of a linear model are proposed. The estimators are based on the resampling techniques cross-validation and bootstrap. The robustness of t...
Jafar A. Khan, Stefan Van Aelst, Ruben H. Zamar
ESANN
2003
13 years 6 months ago
Fast approximation of the bootstrap for model selection
The bootstrap resampling method may be efficiently used to estimate the generalization error of a family of nonlinear regression models, as artificial neural networks. The main dif...
Geoffroy Simon, Amaury Lendasse, Vincent Wertz, Mi...
WSC
2001
13 years 6 months ago
Resampling methods for input modeling
Stochastic simulation models are used to predict the behavior of real systems whose components have random variation. The simulation model generates artificial random quantities b...
Russell R. Barton, Lee Schruben
CSDA
2008
94views more  CSDA 2008»
13 years 4 months ago
Robust model selection using fast and robust bootstrap
Robust model selection procedures control the undue influence that outliers can have on the selection criteria by using both robust point estimators and a bounded loss function wh...
Matias Salibian-Barrera, Stefan Van Aelst
IPMI
2009
Springer
13 years 11 months ago
Estimating the Confidence of Statistical Model Based Shape Prediction
We propose a method for estimating confidence regions around shapes predicted from partial observations, given a statistical shape model. Our method relies on the estimation of the...
Rémi Blanc, Ekaterina Syrkina, Gábor...