Sequential Implementation of Monte Carlo Tests With Uniformly Bounded Resampling Risk

@article{Gandy2009SequentialIO,
  title={Sequential Implementation of Monte Carlo Tests With Uniformly Bounded Resampling Risk},
  author={A. Gandy},
  journal={Journal of the American Statistical Association},
  year={2009},
  volume={104},
  pages={1504 - 1511}
}
  • A. Gandy
  • Published 2009
  • Mathematics
  • Journal of the American Statistical Association
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 nonsequential algorithms, using a bounded sample size, do not have this property. Although the algorithm is open-ended, the expected number of steps is finite… Expand
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