The work this thesis focuses on the choice of the smoothing parameter in the context of non-parametric estimation of the density function for stationary ergodic continuous time processes. The accuracy of the estimation depends greatly on the choice of this parameter. The main goal of this work is to build an automatic window selection procedure and establish asymptotic properties while considering a general dependency framework that can be easily used in practice. The manuscript is divided into three parts. The first part reviews the literature on the subject, set the state of the art and discusses our contribution in within. In the second part, we design an automatical method for selecting the smoothing parameter when the density is estima...
We present in this thesis, the non-parametric approach using mixed associated kernels for densities ...
International audienceIn this paper, we are interested in the problem of smoothing parameter select...
A nonparametric method for the estimation of the Lévy density of a process X is developed. Estimato...
Les travaux de cette thèse portent sur le choix du paramètre de lissage dans le problème de l'estima...
The work of this thesis focuses upon some nonparametric estimation problems. More precisely, conside...
This thesis consists of five papers (Papers A-E) treating problems in non-parametric statistics, esp...
The present PhD deals with nonparametric regression using repeated measurements data. On the one han...
International audienceWe consider the problem of the optimal selection of the smoothing parameter $h...
Kernel density estimation is one of the main methods available for univariate density estimation. Th...
International audienceIn this work we consider the class of symmetricalpha stable processes which ar...
In this paper, we consider a generalised kernel smoothing estimator of the regression function with ...
Dans cette thèse, nous nous intéressons à l'estimation non paramétrique de la densité conditionnelle...
Ce travail est consacré au problème d'estimation non paramétrique dans des modèles de régression en ...
International audienceOn the basis of a poisson sampling, we estimate the spectral density of a cont...
Aspects of estimation of the (marginal) probability density for a stationary sequence or continuous ...
We present in this thesis, the non-parametric approach using mixed associated kernels for densities ...
International audienceIn this paper, we are interested in the problem of smoothing parameter select...
A nonparametric method for the estimation of the Lévy density of a process X is developed. Estimato...
Les travaux de cette thèse portent sur le choix du paramètre de lissage dans le problème de l'estima...
The work of this thesis focuses upon some nonparametric estimation problems. More precisely, conside...
This thesis consists of five papers (Papers A-E) treating problems in non-parametric statistics, esp...
The present PhD deals with nonparametric regression using repeated measurements data. On the one han...
International audienceWe consider the problem of the optimal selection of the smoothing parameter $h...
Kernel density estimation is one of the main methods available for univariate density estimation. Th...
International audienceIn this work we consider the class of symmetricalpha stable processes which ar...
In this paper, we consider a generalised kernel smoothing estimator of the regression function with ...
Dans cette thèse, nous nous intéressons à l'estimation non paramétrique de la densité conditionnelle...
Ce travail est consacré au problème d'estimation non paramétrique dans des modèles de régression en ...
International audienceOn the basis of a poisson sampling, we estimate the spectral density of a cont...
Aspects of estimation of the (marginal) probability density for a stationary sequence or continuous ...
We present in this thesis, the non-parametric approach using mixed associated kernels for densities ...
International audienceIn this paper, we are interested in the problem of smoothing parameter select...
A nonparametric method for the estimation of the Lévy density of a process X is developed. Estimato...