[Statlist] Reminder: ETH Young Data Science Researcher Seminar Zurich - virtual seminar with Muriel Pérez, Centrum Wiskunde & Informatica (CWI), Amsterdam - Wednesday, 26 October 2022

Kaiser-Heinzmann Susanne @u@@nne@k@|@er @end|ng |rom @t@t@m@th@ethz@ch
Mon Oct 24 11:22:31 CEST 2022


We are glad to announce the following virtual talk in the ETH Young Data Science Researcher Seminar Zurich

"E-statistics, group invariance and anytime-valid testing“  
by Muriel Pérez, Centrum Wiskunde & Informatica (CWI), Amsterdam

Date and Time: Wednesday, 26 October 2022, 16:00-17:00 (Zurich time)
Place:  Zoom at https://ethz.zoom.us/j/68998616059, Meeting ID: 689 9861 6059

Abstract: We study worst-​case-growth-rate-optimal (GROW) E-​statistics for hypothesis testing between two dominated group models. If the underlying group G acts freely on the observation space, there exists a maximally invariant statistic of the data. We show that among all E-​statistics, invariant or not, the likelihood ratio of the maximally invariant statistic is GROW and that an anytime-​valid test can be based on it. By virtue of a representation theorem of Wijsman, the GROW E-​statistic is equivalent to a Bayes factor with a right Haar prior on G. Such Bayes factors are known to have good frequentist and Bayesian properties. We show that reductions through sufficiency and invariance can be made in tandem without affecting optimality. A crucial assumption on the group G is its amenability, a well-​known group-​theoretical condition, which holds, for instance, in general scale-​location families. Our results also apply to finite-​dimensional linear regression.

Organisers: Alexander Henzi, Michael Law, Xinwei Shen


Seminar website: https://math.ethz.ch/sfs/news-and-events/young-data-science.html

Young Data Science Researcher Seminar Zurich – Seminar for Statistics | ETH Zurich
math.ethz.ch




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