1 citations · 1 across the 4 of their papers we have counts for
4 papers · 1 filter
Sequential Conditional Independence Testing with Machine Learning Models
Angel Reyero-Lobo, Michele Meziu, Sebastian Uriel Arias +1
Conditional independence testing is a ubiquitous problem in scientific discovery. The widely employed model-X assumption shifts the modelling burden from the dependence of the outp…
Rao-Blackwellized e-variables
Dante de Roos, Ben Chugg, Peter Grünwald +1
We show that for any concave utility, the expected utility of an e-variable can only increase after conditioning on a sufficient statistic, echoing the classic Rao-Blackwell theore…
On admissibility in post-hoc hypothesis testing
Ben Chugg, Tyron Lardy, Aaditya Ramdas +1
The validity of classical hypothesis testing requires the significance level be fixed before any statistical analysis takes place. This is a stringent requirement. For instance…
Almost the Best of Three Worlds: Risk, Consistency and Optional Stopping for the Switch Criterion in Nested Model Selection
Stéphanie van der Pas, Peter Grünwald
We study the switch distribution, introduced by Van Erven et al. (2012), applied to model selection and subsequent estimation. While switching was known to be strongly consistent,…