Min-max approach for comparison of univariate normality tests.

Comparison of normality tests based on absolute or average powers are bound to give ambiguous results, since these statistics critically depend upon the alternative distribution which cannot be specified. A test which is optimal against a certain type of alternatives may perform poorly against other...

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Autor principal:	Tanweer Ul Islam
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6caa375da6764224b1389c329a60d376
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spelling	oai:doaj.org-article:6caa375da6764224b1389c329a60d3762021-12-02T20:18:47ZMin-max approach for comparison of univariate normality tests.1932-620310.1371/journal.pone.0255024https://doaj.org/article/6caa375da6764224b1389c329a60d3762021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255024https://doaj.org/toc/1932-6203Comparison of normality tests based on absolute or average powers are bound to give ambiguous results, since these statistics critically depend upon the alternative distribution which cannot be specified. A test which is optimal against a certain type of alternatives may perform poorly against other alternative distributions. Thus, an invariant benchmark is proposed in the recent normality literature by computing Neyman-Pearson tests against each alternative distribution. However, the computational cost of this benchmark is significantly high, therefore, this study proposes an alternative approach for computing the benchmark. The proposed min-max approach reduces the calculation cost in terms of computing and estimating the Neyman-Pearson tests against each alternative distribution. An extensive simulation study is conducted to evaluate the selected normality tests using the proposed methodology. The proposed min-max method produces similar results in comparison with the benchmark based on Neyman-Pearson tests but at a low computational cost.Tanweer Ul IslamPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0255024 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tanweer Ul Islam Min-max approach for comparison of univariate normality tests.
description	Comparison of normality tests based on absolute or average powers are bound to give ambiguous results, since these statistics critically depend upon the alternative distribution which cannot be specified. A test which is optimal against a certain type of alternatives may perform poorly against other alternative distributions. Thus, an invariant benchmark is proposed in the recent normality literature by computing Neyman-Pearson tests against each alternative distribution. However, the computational cost of this benchmark is significantly high, therefore, this study proposes an alternative approach for computing the benchmark. The proposed min-max approach reduces the calculation cost in terms of computing and estimating the Neyman-Pearson tests against each alternative distribution. An extensive simulation study is conducted to evaluate the selected normality tests using the proposed methodology. The proposed min-max method produces similar results in comparison with the benchmark based on Neyman-Pearson tests but at a low computational cost.
format	article
author	Tanweer Ul Islam
author_facet	Tanweer Ul Islam
author_sort	Tanweer Ul Islam
title	Min-max approach for comparison of univariate normality tests.
title_short	Min-max approach for comparison of univariate normality tests.
title_full	Min-max approach for comparison of univariate normality tests.
title_fullStr	Min-max approach for comparison of univariate normality tests.
title_full_unstemmed	Min-max approach for comparison of univariate normality tests.
title_sort	min-max approach for comparison of univariate normality tests.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/6caa375da6764224b1389c329a60d376
work_keys_str_mv	AT tanweerulislam minmaxapproachforcomparisonofunivariatenormalitytests
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Min-max approach for comparison of univariate normality tests.

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