activity
20152026
most citedKernel based method for the -sample problem

2 citations · 5 across the 18 of their papers we have counts for

collaborators

24 papers

stat.ME2026

Testing for point-impact effects in a spatial semi-functional linear regression model

Stéphane Bouka, Emmanuel De Dieu Nkou, Alban Mbina Mbina +1

This paper introduces a novel semiparametric testing framework for localized point-impact effects within a spatial semi-functional linear regression model. We address an intricate…

math.ST2025

Nonparametric estimation of sliced inverse regression by the -nearest neighbors kernel method

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

We investigate nonparametric estimation of sliced inverse regression (SIR) via the -nearest neighbors approach with a kernel. An estimator of the covariance matrix of the condit…

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.ST2023★ 1 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

On estimation and prediction in a spatial semi-functional linear regression model

Stéphane Bouka, Kowir Pambo Bello, Guy Martial Nkiet

We tackle estimation and prediction at non-visted sites in a spatial semi-functional linear regression model with derivatives that combines a functional linear model with a nonpara…

math.ST2022

An independence test for functional variables based on kernel normalized cross-covariance operator

Terence Kevin Manfoumbi Djonguet, Guy Martial Nkiet

We propose an independence test for random variables valued into metric spaces by using a test statistic obtained from appropriately centering and rescaling the squared Hilbert-Sch…

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.…

math.ST2022

Testing independence of functional variables by an Hilbert-Schmidt independence criterion estimator

Terence Kevin Manfoumbi Djonguet, Guy Martial Nkiet, Alban Mbina Mbina

We propose an estimator of the Hilbert-Schmidt Independence Criterion obtained from an appropriate modification of the usual estimator. We then get asymptotic normality of this est…

math.ST2020

Wavelet-based estimation in a semiparametric regression model

Emmanuel de Dieu Nkou, Guy Martial Nkiet

In this paper, we introduce a wavelet-based method for estimating the EDR space in Li's semiparametric regression model for achieving dimension reduction. This method is obtained b…

math.ST2020

Asymptotic normality of a generalized maximum mean discrepancy estimator

Armando Sosthene Kali Balogoun, Guy Martial Nkiet, Carlos Ogouyandjou

In this paper, we propose an estimator of the generalized maximum mean discrepancy between several distributions, constructed by modifying a naive estimator. Asymptotic normality i…

math.ST2019

Robustifying multiple-set linear canonical analysis with S-estimator

Ulrich Djemby Bivigou, Guy Martial Nkiet

We consider a robust version of multiple-set linear canonical analysis obtained by using a S-estimator of covariance operator. The related influence functions are derived. Asymptot…

math.ST2019

Dimension reduction in spatial regression with kernel SAVE method

Mètolidji Moquilas Raymond Affossogbe, Guy Martial Nkiet, Carlos Ogouyandjou

We consider the smoothed version of sliced average variance estimation (SAVE) dimension reduction method for dealing with spatially dependent data that are observations of a strong…

math.ST2019

On estimation and prediction in spatial functional linear regression model

Stéphane Bouka, Sophie Dabo-Niang, Guy Martial Nkiet

We consider a spatial functional linear regression, where a scalar response is related to a square integrable spatial functional process. We use a smoothing spline estimator for th…

math.ST2018★ 2 cited

Kernel based method for the -sample problem

Armando Sosthene Kali Balogoun, Guy Martial Nkiet, Carlos Ogouyandjou

In this paper we deal with the problem of testing for the equality of probability distributions defined on , where is a metric space an…

math.ST2018★ 2 cited

-Sample problem based on generalized maximum mean discrepancy

Armando Sosthene Kali Balogoun, Guy Martial Nkiet, Carlos Ogouyandjou

In this paper we deal with the problem of testing for the quality of probability distributions. We introduce a generalization of the maximum mean discrepancy that permits to ch…

math.ST2018

Smoothed functional average variance estimation for dimension reduction

MÈtolidji Moquilas Raymond Affossogbe, Guy Martial Nkiet, Carlos Ogouyandjou

We propose an estimation method that we call functional average variance estimation (FAVE), for estimating the EDR space in functional semiparametric regression model, based on ker…

math.ST2018

Robust multiple-set linear canonical analysis based on minimum covariance determinant estimator

Ulrich Djemby Bivigou, Guy Martial Nkiet

By deriving influence functions related to multiple-set linear canonical analysis (MSLCA) we show that the classical version of this analysis, based on empirical covariance operato…

math.ST2018

Strong consistency of kernel estimator in a semiparametric regression model

Emmanuel De Dieu Nkou, Guy Martial Nkiet

Estimating the effective dimension reduction (EDR) space, related to the semiparametric regression model introduced by Li \cite{sir}, is based on the estimation of the covariance m…

math.ST2017

Asymptotic theory of multiple-set linear canonical analysis

Guy Martial Nkiet

This paper deals with asymptotics for multiple-set linear canonical analysis (MSLCA). A definition of this analysis, that adapts the classical one to the context of Euclidean rando…

math.ST2017

Variable selection in discriminant analysis for mixed variables and several groups

Alban Mbina Mbina, Guy Martial Nkiet, Fulgence Eyi Obiang

We propose a method for variable selection in discriminant analysis with mixed categorical and continuous variables. This method is based on a criterion that permits to reduce the…

math.ST2015

Variable selection in multiple regression with random design

Alban Mbina Mbina, Guy Martial Nkiet, Assi Nguessan

We propose a method for variable selection in multiple regression with random predictors. This method is based on a criterion that permits to reduce the variable selection problem…