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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....

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Detalles Bibliográficos
Autores principales: Hemerik, Jesse, Goeman, Jelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
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.
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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
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