255 citations · 1.8k across the 44 of their papers we have counts for
46 papers
Cellwise Robust Discriminant Analysis
Fabio Centofanti, Can Hakan Dagidir, Mia Hubert +1
Classical discriminant analysis (DA) is based on the mean and empirical covariance matrix of each class, both of which are sensitive to outliers in the data. In the past the focus…
Cellwise and Casewise Robust Multivariate Regression with Inference
Fabio Centofanti, Mia Hubert, Peter J. Rousseeuw
Multivariate linear regression is a fundamental statistical task, but classical estimators such as ordinary least squares are highly sensitive to outliers. These may occur as casew…
Least trimmed squares regression with missing values and cellwise outliers
Jakob Raymaekers, Peter J. Rousseeuw
Regression is the workhorse of statistics, and is often faced with real data that contain outliers. When these are casewise outliers, that is, cases that are entirely wrong or belo…
Robust measures of dispersion for circular data with an anomaly detection rule
Houyem Demni, Mia Hubert, Giovanni C. Porzio +1
Circular variables that represent directions or periodic observations arise in many fields, such as biology and environmental sciences. An important issue when dealing with circula…
The bixplot: A variation on the boxplot suited for bimodal data
Camille M. Montalcini, Peter J. Rousseeuw
Boxplots and related visualization methods are widely used exploratory tools for taking a first look at collections of univariate variables. In this note an extension is provided t…
Kernel Outlier Detection
Can Hakan Dağıdır, Mia Hubert, Peter J. Rousseeuw
A new anomaly detection method called kernel outlier detection (KOD) is proposed. It is designed to address challenges of outlier detection in high-dimensional settings. The aim is…