Rejoinder to the discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”
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We thank the Editor, Tommaso Proietti, for the invitation to write a discussion paper and for encouraging such a wide ranging discussion. We also thank the Associate Editor in charge of the discussion, Alessio Farcomeni, for his very careful work.
We feel humbled by the quantity of insightful comments stimulated by our paper and that so many prominent researchers in the field of robust statistics were kind enough to contribute to the discussion. We are also highly surprised (and very glad) to see that the length of the discussion is twice the length of the original paper!
We thank all the discussants for their supportive comments and for their appreciation of our work. Therefore, we take the discussion as a good sign that the “philosophy” of monitoring will have more fans in the future. We believe that the discussions include contributions that are worth considering per se: improvements of existing methodologies; extensions to multi-parameter monitoring; a new \(\rho \)
The work has been partially supported by the European Commission’s Hercule III programme 2014–2020 through the Automated Monitoring Tool project. This research benefits from the HPC (High Performance Computing) facility of the University of Parma, Italy. M.R. gratefully acknowledges support from the CRoNoS project, reference CRoNoS COST Action IC1408.
- Cerioli A, Atkinson AC, Riani M (2016) How to marry robustness and applied statistics. In: Di Battista T, Moreno E, Racugno W (eds) Topics on methodological and applied statistical inference. Springer, Heidelberg, pp 51–64Google Scholar
- Riani M, Atkinson AC, Cerioli A, Corbellini A (2018) Robust methods via monitoring for clustering and multivariate data analysis. SubmittedGoogle Scholar