Sequential Implementation of Monte Carlo Tests With Uniformly Bounded Resampling Risk
Sequential Implementation of Monte Carlo Tests With Uniformly Bounded Resampling Risk
This paper introduces an open-ended sequential algorithm for computing the p-value of a test using Monte Carlo simulation. It guarantees that the resampling risk, the probability of a different decision than the one based on the theoretical p-value, is uniformly bounded by an arbitrarily small constant. Previously suggested sequential or …