1 citations · 1 across the 7 of their papers we have counts for
7 papers
Improving online FDR procedures via online analogs of e-closure and compound e-values
Ziyu Xu, Lasse Fischer, Aaditya Ramdas
In many scientific applications, hypotheses are generated and tested continuously in a stream. We develop a framework for improving online multiple testing procedures with false di…
Bringing Closure to False Discovery Rate Control: A General Principle for Multiple Testing
Ziyu Xu, Aldo Solari, Lasse Fischer +3
We present a novel necessary and sufficient principle for multiple testing methods controlling an expected loss. This principle asserts that every such multiple testing method is a…
Improving Wald's (approximate) sequential probability ratio test by avoiding overshoot
Lasse Fischer, Aaditya Ramdas
Wald's sequential probability ratio test (SPRT) is a cornerstone of sequential analysis. Based on desired type-I, II error levels , it stops when the likelihood ratio crosses…
An online generalization of the (e-)Benjamini-Hochberg procedure
Lasse Fischer, Ziyu Xu, Aaditya Ramdas
In online multiple testing, the hypotheses arrive one by one, and at each time we must immediately reject or accept the current hypothesis solely based on the data and hypotheses o…
Admissible online closed testing must employ e-values
Lasse Fischer, Aaditya Ramdas
In contemporary research, data scientists often test an infinite sequence of hypotheses one by one, and are required to make real-time decisions without knowing th…
Multiple testing with anytime-valid Monte Carlo p-values
Lasse Fischer, Timothy Barry, Aaditya Ramdas
In contemporary problems involving genetic or neuroimaging data, thousands of hypotheses need to be tested. Due to their high power, and finite sample guarantees on type-I error un…
Sequential Monte-Carlo testing by betting
Lasse Fischer, Aaditya Ramdas
In a Monte-Carlo test, the observed dataset is fixed, and several resampled or permuted versions of the dataset are generated in order to test a null hypothesis that the original d…