We propose elliptical graphical models based on conditional uncorrelatedness as a robust generalization of Gaussian graphical models. Letting the population distribution be elliptical instead of normal allows the fitting of data with arbitrarily heavy tails. We study the class of proportionally...

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between...

A fast update algorithm for online calculation of the Qn scale estimator is presented. This algorithm allows robust analysis of high-frequency time series in real time. It provides reliable estimates of a time-varying volatility even if many large outliers are present and it offers good...