Hypothesis testing with e-values


Testing statistical hypothesis is usually done in sciences using p-values. In this project we promote using e-values, which are Bayes factors stripped of their Bayesian content. In some respects they are more convenient: e.g., the arithmetic mean of e-values is again an e-value, whereas merging p-values is more difficult. To a large degree, we are motivated by the algorithmic theory of randomness, which has both p-tests (introduced by Per Martin-Löf) and e-tests (introduced by Leonid Levin).

Working Papers

This page is maintained by Vladimir Vovk.   Last modified on 4 March 2020