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Random thresholds for linear model selection

Marc Lavielle 1 Carenne Ludeña
1 SELECT - Model selection in statistical learning
LMO - Laboratoire de Mathématiques d'Orsay, Inria Saclay - Ile de France
Abstract : A method is introduced to estimate the number of significant coefficients in non ordered model selection problems. The method is based on a convenient random centering of the partial sums of the ordered observations. Based on $L-$statistics methods we show consistency of the proposed estimator. An extension to unknown parametric distributions is considered. The method is then applied to a regression model and interpreted as a random threshold procedure. Simulated examples are included to show the accuracy of the estimator.
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Submitted on : Friday, May 19, 2006 - 8:28:46 PM
Last modification on : Wednesday, April 20, 2022 - 3:37:38 AM
Long-term archiving on: : Sunday, April 4, 2010 - 9:12:37 PM


  • HAL Id : inria-00070434, version 1


Marc Lavielle, Carenne Ludeña. Random thresholds for linear model selection. RR-5572, INRIA. 2005, pp.23. ⟨inria-00070434⟩



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