Research Group "Stochastic Algorithms and Nonparametric Statistics"

Research Seminar "Mathematical Statistics" SS 2021

14.04.2021 N.N.

21.04.2021 Hans-Georg Müller (UC Davis)
exceptionally at 9 a.m.! tba
28.04.2021 N.N.

05.05.2021 N.N.

12.05.2021 N.N.

19.05.2021 Hannes Leeb (University of Vienna)
A (tight) upper bound for the length of confidence intervals with conditional coverage
We show that two popular selective inference procedures, namely data carving (Fithian et al., 2017) and selection with a randomized response (Tian et al., 2018b), when combined with the polyhedral method (Lee et al., 2016), result in confidence intervals whose length is bounded. This contrasts results for confidence intervals based on the polyhedral method alone, whose expected length is typically infinite (Kivaranovic and Leeb, 2020). Moreover, we show that these two procedures always dominate corresponding sample-splitting methods in terms of interval length.
26.05.2021 N.N.

02.06.2021 N.N.

09.06.2021 Victor Panaretos (EPFL Lausanne)
tba
16.06.2021 N.N.

23.06.2021 N.N.

30.06.2021 N.N.

07.07.2021 N.N.

14.07,2021 N.N.



last reviewed: April 6, 2021 by Christine Schneider