Add to ORKGPrecise asymptotic descriptions of the minimax affine risks and bias-variance tradeoffs for estimating linear functionals are given for a broad class of moduli. The results are complemented by illustrative examples including one where it is possible to construct an estimator which is fully adaptive over a range of parameter spaces. 1. Introduction. W
International audienceThis paper deals with the estimation of a autoregression function at a given p...
In this paper, we observe a sparse mean vector through Gaussian noise and we aim at estimating some ...
Abstract:. We introduce two novel procedures to test the nullity of the slope function in the functi...
Precise asymptotic descriptions of the minimax affine risks and bias-variance tradeoffs for estimati...
The minimax theory for estimating linear functionals is extended to the case of a finite union of co...
Adaptive estimation of linear functionals over a collection of parameter spaces is considered. A bet...
AbstractWe consider estimation of the parameter B in a multivariate linear functional relationship X...
We consider the estimation of the value of a linear functional of the slope parameter in functional ...
A nonparametric adaptation theory is developed for the construction of confidence intervals for line...
AbstractThe problem of estimating linear functionals based on Gaussian observations is considered. P...
A nonparametric adaptation theory is developed for the construction of confidence intervals for line...
International audienceWe consider the problem of estimation of a linear functional in the Gaussian s...
Adaptive estimation of a quadratic functional over both Besov and Lp balls is considered. A collecti...
This thesis is devoted to nonparametric estimation for autoregressive models. We consider the proble...
This paper continues the research started in Lepski and Willer (2016). In the framework of the convo...
International audienceThis paper deals with the estimation of a autoregression function at a given p...
In this paper, we observe a sparse mean vector through Gaussian noise and we aim at estimating some ...
Abstract:. We introduce two novel procedures to test the nullity of the slope function in the functi...
Precise asymptotic descriptions of the minimax affine risks and bias-variance tradeoffs for estimati...
The minimax theory for estimating linear functionals is extended to the case of a finite union of co...
Adaptive estimation of linear functionals over a collection of parameter spaces is considered. A bet...
AbstractWe consider estimation of the parameter B in a multivariate linear functional relationship X...
We consider the estimation of the value of a linear functional of the slope parameter in functional ...
A nonparametric adaptation theory is developed for the construction of confidence intervals for line...
AbstractThe problem of estimating linear functionals based on Gaussian observations is considered. P...
A nonparametric adaptation theory is developed for the construction of confidence intervals for line...
International audienceWe consider the problem of estimation of a linear functional in the Gaussian s...
Adaptive estimation of a quadratic functional over both Besov and Lp balls is considered. A collecti...
This thesis is devoted to nonparametric estimation for autoregressive models. We consider the proble...
This paper continues the research started in Lepski and Willer (2016). In the framework of the convo...
International audienceThis paper deals with the estimation of a autoregression function at a given p...
In this paper, we observe a sparse mean vector through Gaussian noise and we aim at estimating some ...
Abstract:. We introduce two novel procedures to test the nullity of the slope function in the functi...