Online Program Home
  My Program

Abstract Details

Activity Number: 178 - Contributed Poster Presentations: Royal Statistical Society
Type: Contributed
Date/Time: Monday, July 31, 2017 : 10:30 AM to 12:20 PM
Sponsor: Royal Statistical Society
Abstract #325426
Title: Implementing Monte Carlo Tests with Multiple Thresholds
Author(s): Georg Hahn* and Axel Gandy and Dong Ding
Companies: Imperial College London and Imperial College London and Imperial College London
Keywords: Algorithm ; Finite time ; Hypothesis ; P-value ; Significance

Software packages usually report the significance of statistical tests using p-values. We are interested in computing the significance of a hypothesis H with respect to several thresholds simultaneously -- with the caveat that the p-value p corresponding to H is unknown and can only be approximated using Monte Carlo simulation. Instead of considering a set of thresholds, this poster presents a more general construction which allows to compute a decision of p with respect to user-specified intervals (called "p-value buckets"): Whereas non-overlapping buckets lead to classical decisions in expected infinite runtime, suitably chosen overlapping buckets allow guaranteed decisions in finite time which are reported in a new fashion that extends the widespread */**/*** significance notation.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

Copyright © American Statistical Association