This paper is concerned with the construction and analysis of a universal estimator for the
regression problem in supervised learning. Universal means that the estimator does not …

We introduce and analyze numerical methods for the treatment of inverse problems, based
on an adaptive wavelet Galerkin discretization. These methods combine the theoretical …

This paper is concerned with the regularization of linear ill-posed problems by a
combination of data smoothing and fractional filter methods. For the data smoothing, a …

We consider the problem of estimating an unknown function f in a regression setting with
random design. Instead of expanding the function on a regular wavelet basis, we expand it …

The influence of the orbital angular momentum l on the mass distribution of fission fragments
is studied, both on previously available data on heavy ion induced fission and in new …

The nonparametric estimation of density and regression function based on functional
stationary processes using wavelet bases for Hilbert spaces of functions is investigated in …

In this study, we look at the wavelet basis for the nonparametric estimation of density and
regression functions for continuous functional stationary processes in Hilbert space. The …

We discuss a new way of evaluating the performance of a statistical estimation procedure.
This consists of investigating the maximal set where a given procedure has a given rate of …

In this paper, we investigate the minimax properties of Stein block thresholding in any
dimension d with a particular emphasis on d= 2. Towards this goal, we consider a frame …

This paper deals with the problem of multivariate copula density estimation. Using wavelet
methods we provide two shrinkage procedures based on thresholding rules for which …