Add to ORKGA convolution regression model with random design is considered. We investigate the estimation of the derivatives of an unknown function, element of the convolution product. We introduce new estimators based on wavelet methods and provide theoretical guaranties on their good performances
We consider a regression model with errors-in-variables: $(Y,X)$, where $Y=f(Z)+\xi$ and $X=Z+W$. Ou...
We consider a regression model with errors-in-variables: $(Y,X)$, where $Y=f(Z)+\xi$ and $X=Z+W$. Ou...
We investigate function estimation in a nonparametric regression model having the following particul...
A convolution regression model with random design is considered. We investigate the estimation of th...
A convolution regression model with random design is considered. We investigate the estimation of th...
We investigate the estimation of the derivatives of a regression function in the nonparametric regre...
We investigate the estimation of the derivatives of a regression function in the nonparametric regre...
16 pagesWe observe a stochastic process where a convolution product of an unknown function $f$ and a...
International audienceThis paper deals with the problem of estimating the derivatives of a regressio...
International audienceThis paper deals with the problem of estimating the derivatives of a regressio...
24 pWe consider an indirect convolution model where $m$ blurred and noise-perturbed functions $f_1,\...
24 pWe consider an indirect convolution model where $m$ blurred and noise-perturbed functions $f_1,\...
International audienceThe problem of estimating the density-weighted average derivative of a regress...
The nonlinear wavelet estimator of regression function with random design is constructed. The optima...
We propose a method of estimation of the derivatives of probability density based wavelets methods f...
We consider a regression model with errors-in-variables: $(Y,X)$, where $Y=f(Z)+\xi$ and $X=Z+W$. Ou...
We consider a regression model with errors-in-variables: $(Y,X)$, where $Y=f(Z)+\xi$ and $X=Z+W$. Ou...
We investigate function estimation in a nonparametric regression model having the following particul...
A convolution regression model with random design is considered. We investigate the estimation of th...
A convolution regression model with random design is considered. We investigate the estimation of th...
We investigate the estimation of the derivatives of a regression function in the nonparametric regre...
We investigate the estimation of the derivatives of a regression function in the nonparametric regre...
16 pagesWe observe a stochastic process where a convolution product of an unknown function $f$ and a...
International audienceThis paper deals with the problem of estimating the derivatives of a regressio...
International audienceThis paper deals with the problem of estimating the derivatives of a regressio...
24 pWe consider an indirect convolution model where $m$ blurred and noise-perturbed functions $f_1,\...
24 pWe consider an indirect convolution model where $m$ blurred and noise-perturbed functions $f_1,\...
International audienceThe problem of estimating the density-weighted average derivative of a regress...
The nonlinear wavelet estimator of regression function with random design is constructed. The optima...
We propose a method of estimation of the derivatives of probability density based wavelets methods f...
We consider a regression model with errors-in-variables: $(Y,X)$, where $Y=f(Z)+\xi$ and $X=Z+W$. Ou...
We consider a regression model with errors-in-variables: $(Y,X)$, where $Y=f(Z)+\xi$ and $X=Z+W$. Ou...
We investigate function estimation in a nonparametric regression model having the following particul...