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BibTex format

@article{Ding:2020:10.1007/s00180-019-00927-6,
author = {Ding, D and Gandy, A and Hahn, G},
doi = {10.1007/s00180-019-00927-6},
journal = {Computational Statistics},
pages = {1373--1392},
title = {A simple method for implementing Monte Carlo tests},
url = {http://dx.doi.org/10.1007/s00180-019-00927-6},
volume = {35},
year = {2020}
}

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TY  - JOUR
AB  - We consider a statistical test whose p value can only be approximated using Monte Carlo simulations. We are interested in deciding whether the p value for an observed data set lies above or below a given threshold such as 5%. We want to ensure that the resampling risk, the probability of the (Monte Carlo) decision being different from the true decision, is uniformly bounded. This article introduces a simple open-ended method with this property, the confidence sequence method (CSM). We compare our approach to another algorithm, SIMCTEST, which also guarantees an (asymptotic) uniform bound on the resampling risk, as well as to other Monte Carlo procedures without a uniform bound. CSM is free of tuning parameters and conservative. It has the same theoretical guarantee as SIMCTEST and, in many settings, similar stopping boundaries. As it is much simpler than other methods, CSM is a useful method for practical applications.
AU  - Ding,D
AU  - Gandy,A
AU  - Hahn,G
DO  - 10.1007/s00180-019-00927-6
EP  - 1392
PY  - 2020///
SN  - 0943-4062
SP  - 1373
TI  - A simple method for implementing Monte Carlo tests
T2  - Computational Statistics
UR  - http://dx.doi.org/10.1007/s00180-019-00927-6
UR  - https://link.springer.com/article/10.1007%2Fs00180-019-00927-6
UR  - http://hdl.handle.net/10044/1/74476
VL  - 35
ER  -

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Professor Axel Gandy

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