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
Since Stein’s 1956 seminal paper, shrinkage has played a fundamental role in both parametric and non...
We develop asymptotic theory for nonparametric estimators of the autoregression function. To deal wi...
This thesis is devoted to nonparametric estimation for autoregressive models. We consider the proble...
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...
AbstractWe consider estimation of the parameter B in a multivariate linear functional relationship X...
Adaptive estimation of linear functionals over a collection of parameter spaces is considered. A bet...
AbstractThe problem of estimating linear functionals based on Gaussian observations is considered. P...
We discuss extremal problems which arise in various nonparametric statistical settings with Hölder f...
AbstractThis article investigates linear minimax estimators of regression coefficient in a linear mo...
International audienceWe consider the model $Z_i=X_i+\varepsilon_i$ for i.i.d. $X_i$'s and $\varepsi...
In this paper, estimation of a regression function from independent and identically distributed rand...
International audienceWe consider the problem of estimating the slope parameter in circular function...
A nonparametric adaptation theory is developed for the construction of confidence intervals for line...
A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lo...
Since Stein’s 1956 seminal paper, shrinkage has played a fundamental role in both parametric and non...
We develop asymptotic theory for nonparametric estimators of the autoregression function. To deal wi...
This thesis is devoted to nonparametric estimation for autoregressive models. We consider the proble...
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...
AbstractWe consider estimation of the parameter B in a multivariate linear functional relationship X...
Adaptive estimation of linear functionals over a collection of parameter spaces is considered. A bet...
AbstractThe problem of estimating linear functionals based on Gaussian observations is considered. P...
We discuss extremal problems which arise in various nonparametric statistical settings with Hölder f...
AbstractThis article investigates linear minimax estimators of regression coefficient in a linear mo...
International audienceWe consider the model $Z_i=X_i+\varepsilon_i$ for i.i.d. $X_i$'s and $\varepsi...
In this paper, estimation of a regression function from independent and identically distributed rand...
International audienceWe consider the problem of estimating the slope parameter in circular function...
A nonparametric adaptation theory is developed for the construction of confidence intervals for line...
A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lo...
Since Stein’s 1956 seminal paper, shrinkage has played a fundamental role in both parametric and non...
We develop asymptotic theory for nonparametric estimators of the autoregression function. To deal wi...
This thesis is devoted to nonparametric estimation for autoregressive models. We consider the proble...