most citedWeighted lens depth: Some applications to supervised classification

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

math.ST20201 cited

Weighted lens depth: Some applications to supervised classification

Alejandro Cholaquidis, Ricardo Fraiman, Fabrice Gamboa +1

Starting with Tukey's pioneering work in the 1970's, the notion of depth in statistics has been widely extended especially in the last decade. These extensions include high dimensi…

math.ST2020

Level sets of depth measures in abstract spaces

Alejandro Cholaquidis, Ricardo Fraiman, Leonardo Moreno

The lens depth of a point has been recently extended to general metric spaces, which is not the case for most depths. It is defined as the probability of being included in the inte…

math.ST2020

Level set and density estimation on manifolds

Alejandro Cholaquidis, Ricardo Fraiman, Leonardo Moreno

We tackle the problem of the estimation of the level sets L_f(λ) of the density f of a random vector X supported on a smooth manifold M\subsetR^d , from an iid sample of X. To do t…

math.ST2020

Sensitivity analysis in general metric spaces

Fabrice Gamboa, Thierry Klein, Agnès Lagnoux +1

In this paper, we introduce new indices adapted to outputs valued in general metric spaces. This new class of indices encompasses the classical ones; in particular, the so-called S…

math.ST2018

Sensitivity indices for output on a Riemannian manifold

R. Fraiman, F. Gamboa, L. Moreno

In the context of computer code experiments, sensitivity analysis of a complicated input-output system is often performed by ranking the so-called Sobol indices. One reason of the…