The sixtieth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, May 25, 2023.
2–3 PM — Stefano Fortunati (LSS & IPSA) — [slides]
Matched, mismatched and semiparametric inference in elliptical distributions
Any scientific experiment, which aims to gain some knowledge about a real-word phenomenon, starts with the data collection. In statistics, all the available knowledge about a phenomenon of interest is summarized in the probability density function (pdf) of the collected observations. To this end, we define a model as the family of pdfs that are able to statistically characterize the observations. The most used classes of models are the parametric ones which however require the perfect match between the actual data distribution and the assumed model itself. Nevertheless, in practice, a certain amount of mismatch is often inevitable. Therefore, being aware about the possible performance loss that the derived estimator could undergone under model misspecification is of crucial importance. Even more important would be the possibility to overcome this misspecification problem. This can be achieved by adopting the more general semiparametric characterization of the statistical behavior of the collected data. In this seminar we use the set of elliptical distribution as “fil rouge” to analyse the three above-mentioned aspects.
Joint work with F. Gini & M. S. Greco (University of Pisa, Italy), C. D. Richmond (Duke University, USA), A. M. Zoubir (TU Darmstadt, Germany), A. Renaux (L2S/UPS), F. Pascal (L2S/CentraleSupélec).
References:
- S. Fortunati, F. Gini, M. S. Greco and C. D. Richmond, “Performance Bounds for Parameter Estimation under Misspecified Models: Fundamental Findings and Applications”, IEEE Signal Processing Magazine, vol. 34, no. 6, pp. 142-157, Nov. 2017.
- S. Fortunati, F. Gini, M. S. Greco, A. M. Zoubir and and M. Rangaswamy, “Semiparametric Inference and Lower Bounds for Real Elliptically Symmetric Distributions”, IEEE Transactions on Signal Processing, vol. 67, no. 1, pp. 164-177, 1 Jan.1, 2019.
- S. Fortunati, F. Gini, M. S. Greco, A. M. Zoubir and and M. Rangaswamy, “Semiparametric CRB and Slepian-Bangs Formulas for Complex Elliptically Symmetric Distributions”, IEEE Transactions on Signal Processing, vol. 67, no. 20, pp. 5352-5364, 15 Oct.15, 2019.
- S. Fortunati, A. Renaux, F. Pascal, “Robust semiparametric efficient estimators in complex elliptically symmetric distributions”, IEEE Transactions on Signal Processing, vol. 68, pp. 5003-5015, 2020.
Organizing committee: Pierre Barbillon (MIA-Paris), Julien Bect (L2S), Nicolas Bousquet (EDF R&D), Amélie Fau (LMPS), Filippo Gatti (LMPS), Bertrand Iooss (EDF R&D), Alexandre Janon (LMO), Sidonie Lefebvre (ONERA), Didier Lucor (LISN), Emmanuel Vazquez (L2S).
Coordinators: Julien Bect (L2S) & Sidonie Lefebvre (ONERA)
Practical details: the seminar will be held online using Microsoft Teams.
If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay group on Teams, simply send an email and you will be invited. Please specify which email address the invitation must be sent to (this has to be the address associated with your Teams account).
You will find the link to the seminar on the "General" UQSay channel on Teams, approximately 15 minutes before the beginning.
The technical side of things: you can use Teams either directly from your web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.
