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Title: The power of monitoring: How to make the most of a contaminated multivariate sample Authors:  Marco Riani - University of Parma (Italy) [presenting]
Anthony Atkinson - London School of Economics (United Kingdom)
Andrea Cerioli - University of Parma (Italy)
Aldo Corbellini - Faculty of Economics - University of Parma (Italy)
Abstract: Diagnostic tools must rely on robust high-breakdown methodologies to avoid distortion in presence of contamination by outliers. However, a disadvantage of having a single, even if robust, summary of the data is that important choices have to be made prior to the analysis and their effect may be difficult to evaluate. We argue that an effective solution is to look at several pictures, and possibly to a whole movie, of the available data. This is what we obtain by monitoring the results computed through the robust methodology of choice. We show the information gain that monitoring provides in the study of complex data structures through the analysis of multivariate datasets and using different high-breakdown techniques. Our findings support the claim that the principle of monitoring is very flexible and that it can lead to robust estimators that are as efficient as possible. We also address through simulation some of the tricky inferential issues that arise from monitoring.