Por favor, use este identificador para citar o enlazar este ítem: 10.1080/03610918.2019.1610439

Título: Removing skewness and kurtosis by transformation when testing for mean equality
Fecha de publicación: 10-may-2019
Editorial: Taylor and Francis
Cita bibliográfica: Communications in Statistics - Simulation and Computation on 10 May 2019, available online: http://www.tandfonline.com/10.1080/03610918.2019.1610439
Palabras clave: Kurtosis
Skewness
Welch test
Johnson’s transformation
Hall’s transformation
Resumen: A transformation of the Welch statistic to compare means is proposed to correct skewness and kurtosis of parent populations. The results show that this transformation seems to improve the performance of the test in heavy-tailed distributions more than other transformations focused only on skewness. The proposed test outperforms the Welch test in asymmetric heavy-tailed distributions with high heteroscedasticity and it behaves better than the Johnson’s transformation trimmed mean Welch test in normal, near-normal and light-tailed distributions. It may also be a better option when some of the distributions are heavy-tailed and some light-tailed.
Autor/es principal/es: Parra-Frutos, Isabel
Molera Peris, Lourdes
Facultad/Departamentos/Servicios: Métodos Cuantitativos para la Economía y la Empresa
Versión del editor: https://www.tandfonline.com/doi/abs/10.1080/03610918.2019.1610439
URI: http://hdl.handle.net/10201/99907
DOI: 10.1080/03610918.2019.1610439
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 34
Derechos: info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 International
Aparece en las colecciones:Artículos: Métodos Cuantitativos para la Economía y la Empresa

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