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Exact testing with random permutations
When permutation methods are used in practice, often a limited number of random permutations are used to decrease the computational burden. However, most theoretical literature assumes that the whole permutation group is used, and methods based on random permutations tend to be seen as approximate....
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405018/ https://www.ncbi.nlm.nih.gov/pubmed/30930620 http://dx.doi.org/10.1007/s11749-017-0571-1 |
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author | Hemerik, Jesse Goeman, Jelle |
author_facet | Hemerik, Jesse Goeman, Jelle |
author_sort | Hemerik, Jesse |
collection | PubMed |
description | When permutation methods are used in practice, often a limited number of random permutations are used to decrease the computational burden. However, most theoretical literature assumes that the whole permutation group is used, and methods based on random permutations tend to be seen as approximate. There exists a very limited amount of literature on exact testing with random permutations, and only recently a thorough proof of exactness was given. In this paper, we provide an alternative proof, viewing the test as a “conditional Monte Carlo test” as it has been called in the literature. We also provide extensions of the result. Importantly, our results can be used to prove properties of various multiple testing procedures based on random permutations. |
format | Online Article Text |
id | pubmed-6405018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-64050182019-03-27 Exact testing with random permutations Hemerik, Jesse Goeman, Jelle Test (Madr) Original Paper When permutation methods are used in practice, often a limited number of random permutations are used to decrease the computational burden. However, most theoretical literature assumes that the whole permutation group is used, and methods based on random permutations tend to be seen as approximate. There exists a very limited amount of literature on exact testing with random permutations, and only recently a thorough proof of exactness was given. In this paper, we provide an alternative proof, viewing the test as a “conditional Monte Carlo test” as it has been called in the literature. We also provide extensions of the result. Importantly, our results can be used to prove properties of various multiple testing procedures based on random permutations. Springer Berlin Heidelberg 2017-11-30 2018 /pmc/articles/PMC6405018/ /pubmed/30930620 http://dx.doi.org/10.1007/s11749-017-0571-1 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Hemerik, Jesse Goeman, Jelle Exact testing with random permutations |
title | Exact testing with random permutations |
title_full | Exact testing with random permutations |
title_fullStr | Exact testing with random permutations |
title_full_unstemmed | Exact testing with random permutations |
title_short | Exact testing with random permutations |
title_sort | exact testing with random permutations |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405018/ https://www.ncbi.nlm.nih.gov/pubmed/30930620 http://dx.doi.org/10.1007/s11749-017-0571-1 |
work_keys_str_mv | AT hemerikjesse exacttestingwithrandompermutations AT goemanjelle exacttestingwithrandompermutations |