51 citations · 65 across the 13 of their papers we have counts for
6 papers · 1 filter
Statistically Enhanced Learning: a feature engineering framework to boost (any) learning algorithms
Florian Felice, Christophe Ley, Andreas Groll +1
Feature engineering is of critical importance in the field of Data Science. While any data scientist knows the importance of rigorously preparing data to obtain good performing mod…
Elliptical Symmetry Tests in \proglang{R}
Slađana Babić, Christophe Ley, Marko Palangetić
The assumption of elliptical symmetry has an important role in many theoretical developments and applications, hence it is of primary importance to be able to test whether that ass…
The Wasserstein Impact Measure (WIM): a generally applicable, practical tool for quantifying prior impact in Bayesian statistics
Fatemeh Ghaderinezhad, Christophe Ley, Ben Serrien
The prior distribution is a crucial building block in Bayesian analysis, and its choice will impact the subsequent inference. It is therefore important to have a convenient way to…
Optimal tests for elliptical symmetry: specified and unspecified location
Sladana Babic, Laetitia Gelbgras, Marc Hallin +1
Although the assumption of elliptical symmetry is quite common in multivariate analysis and widespread in a number of applications, the problem of testing the null hypothesis of el…
Sine-skewed toroidal distributions and their application in protein bioinformatics
Jose Ameijeiras-Alonso, Christophe Ley
In the bioinformatics field, there has been a growing interest in modelling dihedral angles of amino acids by viewing them as data on the torus. This has motivated, over the past y…
Simple, asymptotically distribution-free, optimal tests for circular reflective symmetry about a known median direction
Christophe Ley, Thomas Verdebout
In this paper, we propose optimal tests for circular reflective symmetry about a fixed median direction. The distributions against which optimality is achieved are the so-called k-…