Résumé
This paper is dedicated to the study of an estimator of the generalized Hoeffding decomposition. We build such an estimator using an empirical Gram-Schmidt approach and derive a consistency rate in a large dimensional setting. We then apply a greedy algorithm with these previous estimators to a sensitivity analysis. We also establish the consistency of this L2-boosting under sparsity assumptions of the signal to be analyzed. The paper concludes with numerica l experiments, that demonstrate the low computational cost of our method, as well as its efficiency on the standard benchmark of sensitivity analysis.
Mots-clés
L2-boosting; convergence; dependent variables; generalized ANOVA decomposition; sensitivity analysis;
Référence
Magali Champion, Gaelle Chastaing, Sébastien Gadat et Clémentine Prieur, « L2-boosting on a generalized Hoeffding decomposition for dependent variables. Application to Sensitivity Analysis », Statistica Sinica, 2014.
Voir aussi
Publié dans
Statistica Sinica, 2014