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...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0255024 |
| _version_ | 1818719205275467776 |
|---|---|
| author | Tanweer Ul Islam |
| author_facet | Tanweer Ul Islam |
| author_sort | Tanweer Ul Islam |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-17T20:03:14Z |
| format | Article |
| id | doaj.art-6caa375da6764224b1389c329a60d376 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-17T20:03:14Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-6caa375da6764224b1389c329a60d3762022-12-21T21:34:24ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01168e025502410.1371/journal.pone.0255024Min-max approach for comparison of univariate normality tests.Tanweer Ul IslamComparison 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.https://doi.org/10.1371/journal.pone.0255024 |
| spellingShingle | Tanweer Ul Islam Min-max approach for comparison of univariate normality tests. PLoS ONE |
| title | 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_short | Min-max approach for comparison of univariate normality tests. |
| title_sort | min max approach for comparison of univariate normality tests |
| url | https://doi.org/10.1371/journal.pone.0255024 |
| work_keys_str_mv | AT tanweerulislam minmaxapproachforcomparisonofunivariatenormalitytests |