Graphical comparison of normality tests for unimodal distribution data
A methodology is proposed to compare the power of normality tests with a wide variety of alternative unimodal distributions. It is based on the representation of a distribution mosaic in which kurtosis varies vertically and skewness horizontally . The mosaic includes distributions such as exponentia...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/125961 |
| Acceso en línea: | https://hdl.handle.net/2117/125961 https://dx.doi.org/10.1080/00949655.2018.1539085 |
| Access Level: | acceso abierto |
| Palabra clave: | Goodness-of-fit tests Nonparametric statistics Goodness - of - Fit Test Power Graphical Techniques Comparing Normality Tests Anderson - Darling Shapiro - Wilk Bondat de l'ajust, Tests de Estadística no paramètrica Àrees temàtiques de la UPC::Matemàtiques i estadística |
| Sumario: | A methodology is proposed to compare the power of normality tests with a wide variety of alternative unimodal distributions. It is based on the representation of a distribution mosaic in which kurtosis varies vertically and skewness horizontally . The mosaic includes distributions such as exponential , Laplace or uniform, with normal occupying the center. S imulation is used to determine the probability of a sample from each distribution in the mosaic being accepted as normal . We demonst rate our proposal by applying it to the analysis and comparison of some of the most well - known tests |
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