activity
20222024
most citedA method for variable selection in a multivariate functional linear regression model

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

math.ST2024

Rates of strong uniform consistency for the -nearest neighbors kernel estimators of density and regression function

Luran Bengono Mintogo, Emmanuel de Dieu Nkou, Guy Martial Nkiet

We adress the problem of consistency of the -nearest neighbors kernel estimators of the density and the regression function in the multivariate case. We get the rates of strong…

math.ST2024

Testing for homogeneity of several functional variables via multiple maximum variance discrepancy

Armando Sosthène Kali Balogoun, Guy Martial Nkiet

This paper adresses the problem of testing for the equality of probability distributions on Hilbert spaces, with . We introduce a generalization of the maximum va…

math.ST20231 cited

A method for variable selection in a multivariate functional linear regression model

Alban Mina Mbina, Guy Martial Nkiet

We propose a new variable selection procedure for a functional linear model with multiple scalar responses and multiple functional predictors. This method is based on basis expansi…

math.ST2023

Variable selection in multivariate regression model for spatially dependent data

Jean Roland Ebende Penda, Stéphane Bouka, Guy Martial Nkiet

This paper deals with variable selection in multivariate linear regression model when the data are observations on a spatial domain being a grid of sites in with $d\…

math.ST2022

Kernel-based method for joint independence of functional variables

Terence Kevin Manfoumbi Djonguet, Guy Martial Nkiet

This work investigates the problem of testing whether functional random variables are jointly independent using a modified estimator of the -variable Hilbert Schmidt Indeped…

math.ST2022

Asymptotic normality of an estimator of kernel-based conditional mean dependence measure

Terence Kevin Manfoumbi Djonguet, Guy Martial Nkiet

We propose an estimator of the kernel-based conditional mean dependence measure obtained from an appropriate modification of a naive estimator based on usual empirical estimators.…