activity
20122022
most citedAn essay on copula modelling for discrete random vectors; or how to pour new wine into old bottles

3 citations · 3 across the 7 of their papers we have counts for

collaborators

10 papers

stat.ME2022

Hellinger-Bhattacharyya cross-validation for shape-preserving multivariate wavelet thresholding

Carlos Aya-Moreno, Gery Geenens, Spiridon Penev

The benefits of the wavelet approach for density estimation are well established in the literature, especially when the density to estimate is irregular or heterogeneous in smoothn…

stat.ME2021

Statistical depth in abstract metric spaces

Gery Geenens, Alicia Nieto-Reyes, Giacomo Francisci

The concept of depth has proved very important for multivariate and functional data analysis, as it essentially acts as a surrogate for the notion a ranking of observations which i…

stat.ME20193 cited

An essay on copula modelling for discrete random vectors; or how to pour new wine into old bottles

Gery Geenens

Copulas have now become ubiquitous statistical tools for describing, analysing and modelling dependence between random variables. Sklar's theorem, "the fundamental theorem of copul…

stat.ME2018

The Hellinger Correlation

Gery Geenens, Pierre Lafaye de Micheaux

In this paper, the defining properties of a valid measure of the dependence between two random variables are reviewed and complemented with two original ones, shown to be more fund…

stat.ME2017

Shape-preserving wavelet-based multivariate density estimation

Carlos Aya Moreno, Gery Geenens, Spiridon Penev

Wavelet estimators for a probability density f enjoy many good properties, however they are not "shape-preserving" in the sense that the final estimate may not be non-negative or i…

math.ST2017

Mellin-Meijer-kernel density estimation on

Gery Geenens

Nonparametric kernel density estimation is a very natural procedure which simply makes use of the smoothing power of the convolution operation. Yet, it performs poorly when the den…