85 citations · 188 across the 7 of their papers we have counts for
4 papers · 1 filter
Characterizing M-estimators
Timo Dimitriadis, Tobias Fissler, Johanna Ziegel
We characterize the full classes of M-estimators for semiparametric models of general functionals by formally connecting the theory of consistent loss functions from forecast evalu…
Osband's Principle for Identification Functions
Timo Dimitriadis, Tobias Fissler, Johanna Ziegel
Given a statistical functional of interest such as the mean or median, a (strict) identification function is zero in expectation at (and only at) the true functional value. Identif…
Honest calibration assessment for binary outcome predictions
Timo Dimitriadis, Lutz Duembgen, Alexander Henzi +2
Probability predictions from binary regressions or machine learning methods ought to be calibrated: If an event is predicted to occur with probability , it should materialize wi…
A safe Hosmer-Lemeshow test
Alexander Henzi, Marius Puke, Timo Dimitriadis +1
This article proposes an alternative to the Hosmer-Lemeshow (HL) test for evaluating the calibration of probability forecasts for binary events. The approach is based on e-values,…