104 citations · 295 across the 16 of their papers we have counts for
20 papers
Bootstrap inference for linear regression between variables that are never jointly observed: application in in vivo experiments
Polina Arsenteva, Mohamed Amine Benadjaoud, Hervé Cardot
In modern experimental science, there is a common problem of estimating the coefficients of a linear regression in a context where the variables of interest cannot be observed simu…
Conditional bias robust estimation of the total of curve data by sampling in a finite population: an illustration on electricity load curves
Hervé Cardot, Anne De Moliner Anne, Camelia Goga
For marketing or power grid management purposes, many studies based on the analysis of the total electricity consumption curves of groups of customers are now carried out by electr…
Estimating finite mixtures of semi-Markov chains: an application to the segmentation of temporal sensory data
Hervé Cardot, Guillaume Lecuelle, Pascal Schlich +1
In food science, it is of great interest to get information about the temporal perception of aliments to create new products, to modify existing ones or more generally to understan…
Modeling temporal treatment effects with zero inflated semi-parametric regression models: the case of local development policies in France
Herve Cardot, Antonio Musolesi
A semi-parametric approach is proposed to estimate the variation along time of the effects of two distinct public policies that were devoted to boost rural development in France ov…
Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?
Hervé Cardot, David Degras
In the current context of data explosion, online techniques that do not require storing all data in memory are indispensable to routinely perform tasks like principal component ana…
Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis
Hervé Cardot, Antoine Godichon-Baggioni
The geometric median covariation matrix is a robust multivariate indicator of dispersion which can be extended without any difficulty to functional data. We define estimators, base…
Online estimation of the geometric median in Hilbert spaces : non asymptotic confidence balls
Hervé Cardot, Peggy Cénac, Antoine Godichon
Estimation procedures based on recursive algorithms are interesting and powerful techniques that are able to deal rapidly with (very) large samples of high dimensional data. The co…
Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially observed trajectories
Hervé Cardot, Anne De Moliner, Camelia Goga
In the near future, millions of load curves measuring the electricity consumption of French households in small time grids (probably half hours) will be available. All these collec…
Calibration and partial calibration on principal components when the number of auxiliary variables is large
H. Cardot, C. Goga, M. -A Shehzad
In survey sampling, calibration is a very popular tool used to make total estimators consistent with known totals of auxiliary variables and to reduce variance. When the number of…
Variance estimation and asymptotic confidence bands for the mean estimator of sampled functional data with high entropy unequal probability sampling designs
Hervé Cardot, Camelia Goga, Pauline Lardin
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the Hájek formula. The interest of thi…
Recursive estimation of the conditional geometric median in Hilbert spaces
Hervé Cardot, Peggy Cénac, Pierre-André Zitt
A recursive estimator of the conditional geometric median in Hilbert spaces is studied. It is based on a stochastic gradient algorithm whose aim is to minimize a weighted L1 criter…
Uniform convergence and asymptotic confidence bands for model-assisted estimators of the mean of sampled functional data
Hervé Cardot, Camelia Goga, Pauline Lardin
When the study variable is functional and storage capacities are limited or transmission costs are high, selecting with survey sampling techniques a small fraction of the observati…
Confidence bands for Horvitz-Thompson estimators using sampled noisy functional data
Hervé Cardot, David Degras, Etienne Josserand
When collections of functional data are too large to be exhaustively observed, survey sampling techniques provide an effective way to estimate global quantities such as the populat…
Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm
Hervé Cardot, Peggy Cénac, Pierre-André Zitt
With the progress of measurement apparatus and the development of automatic sensors it is not unusual anymore to get thousands of samples of observations taking values in high dime…
A fast and recursive algorithm for clustering large datasets with -medians
Hervé Cardot, Peggy Cénac, Jean-Marie Monnez
Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. Borrowing ideas from MacQueen (1967) who introduced a…
Horvitz-Thompson estimators for functional data: asymptotic confidence bands and optimal allocation for stratified sampling
Hervé Cardot, Etienne Josserand
When dealing with very large datasets of functional data, survey sampling approaches are useful in order to obtain estimators of simple functional quantities, without being obliged…
Properties of Design-Based Functional Principal Components Analysis
Hervé Cardot, Mohamed Chaouch, Camelia Goga +1
This work aims at performing Functional Principal Components Analysis (FPCA) with Horvitz-Thompson estimators when the observations are curves collected with survey sampling techni…
Thresholding Projection Estimators in Functional Linear Models
Herve Cardot, Jan Johannes
We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine dimension reduct…
Quantile regression when the covariates are functions
Hervé Cardot, Christophe Crambes, Pascal Sarda
This paper deals with a linear model of regression on quantiles when the explanatory variable takes values in some functional space and the response is scalar. We propose a spline…
CLT in Functional Linear Regression Models
Hervé Cardot, André Mas, Pascal Sarda
We propose in this work to derive a CLT in the functional linear regression model to get confidence sets for prediction based on functional linear regression. The main difficulty i…