20 citations · 45 across the 6 of their papers we have counts for
8 papers
Non-fungible token transactions: data and challenges
Jason B. Cho, Sven Serneels, David S. Matteson
Non-fungible tokens (NFT) have recently emerged as a novel blockchain hosted financial asset class that has attracted major transaction volumes. Investment decisions rely on data a…
Sparse dimension reduction based on energy and ball statistics
Emmanuel Jordy Menvouta, Sven Serneels, Tim Verdonck
As its name suggests, sufficient dimension reduction (SDR) targets to estimate a subspace from data that contains all information sufficient to explain a dependent variable. Ample…
Robust multivariate methods in Chemometrics
Peter Filzmoser, Sven Serneels, Ricardo Maronna +1
This chapter presents an introduction to robust statistics with applications of a chemometric nature. Following a description of the basic ideas and concepts behind robust statisti…
direpack: A Python 3 package for state-of-the-art statistical dimension reduction methods
Emmanuel Jordy Menvouta, Sven Serneels, Tim Verdonck
The direpack package aims to establish a set of modern statistical dimension reduction techniques into the Python universe as a single, consistent package. The dimension reduction…
Cellwise Robust M Regression
Peter Filzmoser, Sebastiaan Höppner, Irene Ortner +2
The cellwise robust M regression estimator is introduced as the first estimator of its kind that intrinsically yields both a map of cellwise outliers consistent with the linear mod…
Projection pursuit based generalized betas accounting for higher order co-moment effects in financial market analysis
Sven Serneels
Betas are possibly the most frequently applied tool to analyze how securities relate to the market. While in very widespread use, betas only express dynamics derived from second mo…
Multivariate Constrained Robust M-Regression for Shaping Forward Curves in Electricity Markets
Peter Leoni, Pieter Segaert, Sven Serneels +1
In this paper, a multivariate constrained robust M-regression (MCRM) method is developed to estimate shaping coefficients for electricity forward prices. An important benefit of th…
Outlyingness: why do outliers lie out?
Michiel Debruyne, Sebastiaan Höppner, Sven Serneels +1
Outlier detection is an inevitable step to most statistical data analyses. However, the mere detection of an outlying case does not always answer all scientific questions associate…