8 citations · 12 across the 5 of their papers we have counts for
4 papers · 1 filter
Testing for the significance of functional covariates in regression models
Samuel Maistre, Valentin Patilea
Regression models with a response variable taking values in a Hilbert space and hybrid covariates are considered. This means two sets of regressors are allowed, one of finite dimen…
Powerful nonparametric checks for quantile regression
Samuel Maistre, Pascal Lavergne, Valentin Patilea
We address the issue of lack-of-fit testing for a parametric quantile regression. We propose a simple test that involves one-dimensional kernel smoothing, so that the rate at which…
A Significance Test for Covariates in Nonparametric Regression
Pascal Lavergne, Samuel Maistre, Valentin Patilea
We consider testing the significance of a subset of covariates in a nonparametric regression. These covariates can be continuous and/or discrete. We propose a new kernel-based test…
Projection-based nonparametric goodness-of-fit testing with functional covariates
Valentin Patilea, Cesar Sanchez-Sellero, Matthieu Saumard
This paper studies the problem of nonparametric testing for the effect of a random functional covariate on a real-valued error term. The covariate takes values in , the H…