5 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…
Cellwise Outliers
Mia Hubert, Jakob Raymaekers, Peter J. Rousseeuw
In statistics and machine learning, the traditional meaning of the terms `outlier' and `anomaly' is a case in the dataset that behaves differently from the bulk of the data, which…
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…
Kernel Outlier Detection
Can Hakan DaÄıdır, 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…