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Main Authors: Ammous, Sinda, Bouaziz, Olivier, Dedecker, Anatole, Dedecker, Jérôme, Methni, Jonathan El, Mellouk, Mohamed, Muri, Florence
Format: Preprint
Published: 2022
Subjects:
Online Access:https://arxiv.org/abs/2211.08784
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author Ammous, Sinda
Bouaziz, Olivier
Dedecker, Anatole
Dedecker, Jérôme
Methni, Jonathan El
Mellouk, Mohamed
Muri, Florence
author_facet Ammous, Sinda
Bouaziz, Olivier
Dedecker, Anatole
Dedecker, Jérôme
Methni, Jonathan El
Mellouk, Mohamed
Muri, Florence
contents The R package robusTest offers corrected versions of several common tests in bivariate statistics. We point out the limitations of these tests in their classical versions, some of which are well known such as robustness or calibration problems, and provide simple alternatives that can be easily used instead. The classical tests and theirs robust alternatives are compared through a small simulation study. The latter emphasizes the superiority of robust versions of the test of interest. Finally, an illustration of correlation's tests on a real data set is also provided.
format Preprint
id arxiv_https___arxiv_org_abs_2211_08784
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle The robusTest package: two-sample tests revisited
Ammous, Sinda
Bouaziz, Olivier
Dedecker, Anatole
Dedecker, Jérôme
Methni, Jonathan El
Mellouk, Mohamed
Muri, Florence
Methodology
The R package robusTest offers corrected versions of several common tests in bivariate statistics. We point out the limitations of these tests in their classical versions, some of which are well known such as robustness or calibration problems, and provide simple alternatives that can be easily used instead. The classical tests and theirs robust alternatives are compared through a small simulation study. The latter emphasizes the superiority of robust versions of the test of interest. Finally, an illustration of correlation's tests on a real data set is also provided.
title The robusTest package: two-sample tests revisited
topic Methodology
url https://arxiv.org/abs/2211.08784