Variational theorems in gnostical theory of uncertain data
Generalised halfspace depth function is proposed. Basic properties of this depth function including the strong consistency are studied. We show, on several examples that our depth function may be considered to be more appropriate for nonsymetric distributions or for mixtures of distributions.
In nonparametric statistics a classical optimality criterion for estimation procedures is provided by the minimax rate of convergence. However this point of view can be subject to controversy as it requires to look for the worst behavior of an estimation procedure in a given space. The purpose of this paper is to introduce a new criterion based on generic behavior of estimators. We are here interested in the rate of convergence obtained with some classical estimators on almost every, in the sense...
The asymptotic behaviour of ε-entropy of classes of Lipschitz functions in is obtained. Moreover, the asymptotics of ε-entropy of classes of Lipschitz functions in whose tail function decreases as is obtained. In case p = 1 the relation between the ε-entropy of a given class of probability densities on and the minimax risk for that class is discussed.