12 papers
Cellwise and Casewise Robust Covariance in High Dimensions
Fabio Centofanti, Mia Hubert, Peter J. Rousseeuw
The sample covariance matrix is a cornerstone of multivariate statistics, but it is highly sensitive to outliers. These can be casewise outliers, such as cases belonging to a diffe…
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…
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…
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…