| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10181045 | Comptes Rendus Mathematique | 2016 | 5 Pages |
Abstract
A nonlinear sparse model is defined for selecting impact points in regression problems with functional predictors, and a variable selection procedure based on screening and splitting is proposed. Some asymptotics are stated both for the impact points and for the parameters of the model.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Germán Aneiros, Philippe Vieu,