Add to ORKGThe information inequality has been shown to be an effective tool for providing lower bounds for the minimax risk. Bounds based on the chi-square distance can sometimes offer a considerable improvement especially when applied iteratively. This paper compares these two methods in four examples including the bounded normal mean problem as well as obervations from a Poisson distribution
A general lower bound is developed for the minimax risk when estimating an arbitrary functional. The...
A general lower bound is developed for the minimax risk when estimating an arbitrary functional. The...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...
The information inequality has been shown to be an effective tool for providing lower bounds for the...
This paper compares three methods for producing lower bounds on the minimax risk under quadratic los...
This paper compares three methods for producing lower bounds on the minimax risk under quadratic los...
This paper compares three methods for producing lower bounds on the minimax risk under quadratic los...
This paper presents lower bounds for the minimax risk under quadraticloss, derived from information ...
Abstract—Lower bounds involving -divergences between the underlying probability measures are proved ...
A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lo...
A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lo...
A bound is given for the Bayes risk of an estimator under truncated squared error loss. The bound de...
International audienceThe paper deals with the problem of nonparametric estimating the Lp-norm, p ∈ ...
AbstractMinimax risk inequalities are obtained for the location-parameter classification problem. Fo...
A bound is given for the Bayes risk of an estimator under truncated squared error loss. The bound de...
A general lower bound is developed for the minimax risk when estimating an arbitrary functional. The...
A general lower bound is developed for the minimax risk when estimating an arbitrary functional. The...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...
The information inequality has been shown to be an effective tool for providing lower bounds for the...
This paper compares three methods for producing lower bounds on the minimax risk under quadratic los...
This paper compares three methods for producing lower bounds on the minimax risk under quadratic los...
This paper compares three methods for producing lower bounds on the minimax risk under quadratic los...
This paper presents lower bounds for the minimax risk under quadraticloss, derived from information ...
Abstract—Lower bounds involving -divergences between the underlying probability measures are proved ...
A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lo...
A general constrained minimum risk inequality is derived. Given two densities fθ and f0 we find a lo...
A bound is given for the Bayes risk of an estimator under truncated squared error loss. The bound de...
International audienceThe paper deals with the problem of nonparametric estimating the Lp-norm, p ∈ ...
AbstractMinimax risk inequalities are obtained for the location-parameter classification problem. Fo...
A bound is given for the Bayes risk of an estimator under truncated squared error loss. The bound de...
A general lower bound is developed for the minimax risk when estimating an arbitrary functional. The...
A general lower bound is developed for the minimax risk when estimating an arbitrary functional. The...
In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bo...