An efficient algorithm for T-estimation

Nelo Magalhães (1, 2) , Yves Rozenholc (1, 3)

1 SELECT - Model selection in statistical learning
2 LM-Orsay - Laboratoire de Mathématiques d'Orsay
3 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5

We introduce an efficient and exact algorithm, together with a faster but approximate version, which implements with a sub-quadratic complexity the hold-out derived from T-estimation. We study empirically the performance of this hold-out in the context of density estimation considering well-known competitors (hold-out derived from least-squares or Kullback-Leibler divergence, model selection procedures, etc.) and classical problems including histogram or bandwidth selection. Our algorithms are integrated in a companion R-package called Density.T.HoldOut available on the CRAN

Mots clés: T-estimation; density estimation; hold-out; Density.T.HoldOut; R-package

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

Nelo Magalhães, Yves Rozenholc. An efficient algorithm for T-estimation. 2014. ⟨hal-00986229⟩