AdaPT: An interactive procedure for multiple testing with side information

AdaPT: An interactive procedure for multiple testing with side information

Neyman Seminar
Sep 5, 2018, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Will Fithian, UC Berkeley
We consider the problem of multiple hypothesis testing with generic side information: for each hypothesis we observe both a p-value and some predictor encoding contextual information about the hypothesis. For large-scale problems, adaptively focusing power on the more promising hypotheses (those more likely to yield discoveries) can lead to much more powerful multiple testing procedures. We...