activity
20082026
most citedHigh-Breakdown Robust Multivariate Methods

243 citations · 474 across the 6 of their papers we have counts for

collaborators

6 papers

math.ST2026

Finite-Time Observability of Oscillatory Instabilities in Synchronous p-bit Dynamics

Naoya Onizawa, Shunsuke Koshita, Takahiro Hanyu

Synchronous update schemes in p-bit annealing offer a natural route to massive parallelism, but they can also induce period-2 oscillations that degrade optimization performance. In…

stat.ME2019★ 8 cited

M-type penalized splines with auxiliary scale estimation

Ioannis Kalogridis, Stefan Van Aelst

Penalized spline smoothing is a popular and flexible method of obtaining estimates in nonparametric regression but the classical least-squares criterion is highly susceptible to mo…

stat.ME2018★ 33 cited

Robust functional regression based on principal components

Ioannis Kalogridis, Stefan Van Aelst

Functional data analysis is a fast evolving branch of modern statistics and the functional linear model has become popular in recent years. However, most estimation methods for thi…

stat.CO2018★ 2 cited

Fast Computation of Robust Subspace Estimators

Holger Cevallos-Valdiviezo, Stefan Van Aelst

Dimension reduction is often an important step in the analysis of high-dimensional data. PCA is a popular technique to find the best low-dimensional approximation of high-dimension…

math.ST2009★ 188 cited

Propagation of outliers in multivariate data

Fatemah Alqallaf, Stefan Van Aelst, Victor J. Yohai +1

We investigate the performance of robust estimates of multivariate location under nonstandard data contamination models such as componentwise outliers (i.e., contamination in each…

stat.ME2008★ 243 cited

High-Breakdown Robust Multivariate Methods

Mia Hubert, Peter J. Rousseeuw, Stefan Van Aelst

When applying a statistical method in practice it often occurs that some observations deviate from the usual assumptions. However, many classical methods are sensitive to outliers.…