255 citations · 898 across the 12 of their papers we have counts for
8 papers · 1 filter
Real-time discriminant analysis in the presence of label and measurement noise
Iwein Vranckx, Jakob Raymaekers, Bart De Ketelaere +2
Quadratic discriminant analysis (QDA) is a widely used classification technique. Based on a training dataset, each class in the data is characterized by an estimate of its center a…
Real-time outlier detection for large datasets by RT-DetMCD
Bart De Ketelaere, Mia Hubert, Jakob Raymaekers +2
Modern industrial machines can generate gigabytes of data in seconds, frequently pushing the boundaries of available computing power. Together with the time criticality of industri…
MacroPCA: An all-in-one PCA method allowing for missing values as well as cellwise and rowwise outliers
Mia Hubert, Peter J. Rousseeuw, Wannes Van den Bossche
Multivariate data are typically represented by a rectangular matrix (table) in which the rows are the objects (cases) and the columns are the variables (measurements). When there a…
Minimum Covariance Determinant and Extensions
Mia Hubert, Michiel Debruyne, Peter J. Rousseeuw
The Minimum Covariance Determinant (MCD) method is a highly robust estimator of multivariate location and scatter, for which a fast algorithm is available. Since estimating the cov…
A Measure of Directional Outlyingness with Applications to Image Data and Video
Peter J. Rousseeuw, Jakob Raymaekers, Mia Hubert
Functional data covers a wide range of data types. They all have in common that the observed objects are functions of of a univariate argument (e.g. time or wavelength) or a multiv…
Finding Outliers in Surface Data and Video
Mia Hubert, Jakob Raymaekers, Peter J. Rousseeuw +1
Surface, image and video data can be considered as functional data with a bivariate domain. To detect outlying surfaces or images, a new method is proposed based on the mean and th…
Statistical depth meets computational geometry: a short survey
Peter J. Rousseeuw, Mia Hubert
During the past two decades there has been a lot of interest in developing statistical depth notions that generalize the univariate concept of ranking to multivariate data. The not…
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.…