Given a nonparametric regression model, we assume that the number of covariates d → ∞ but only some of these covariates are relevant for the model. Our goal is to identify the relevant covariates and to obtain some ...

The local polynomial estimator is particularly affected by the curse of di- mensionality. So, the potentialities of such a tool become ineffective for large dimensional applications. Motivated by this, we propose a new ...

The selection of the smoothing parameter represents a crucial step in the local polynomial regression, because of the implications on the consistency of the nonparametric regression estimator and because of the difficulties ...