Robust Brown-Forsythe and Robust Modified Brown-Forsythe ANOVA Tests Under Heteroscedasticity for Contaminated Weibull Distribution

• DERYA KARAGÖ ^[1] ; TÜLAY SARAÇBASI ^[1]
  1. [1] Hacettepe University

     Hacettepe University

     Turquía

     
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 39, Nº. 1, 2016, págs. 17-32
• Idioma: inglés
• DOI: 10.15446/rce.v39n1.55135
• Títulos paralelos:
  • ANOVAS robustos heterocedásticos Brown-Forsythe y Brown-Forsythe modificado para la distribución Weibull contaminada
• Enlaces
  • Texto completo
• Resumen
  • español

    En este estudio se proponen tests Brown-Forsythe y robustos Brown-Forsythe ANOVA para tener en cuenta la no-normalidad en datos debida a la presencia de datos atípicos. Se asume que los datos no-normales tienen una distribución Weibull de dos parámetros. Estos tests se construyen en base a estimadores robustos de media y varianza obtenidos con métodos basados en la mediana en vez de métodos de máxima verosimilitud. Se examina en comportamiento de estos tests con datos simulados. Los resultados muestran que éstos tienen un buen desempeño, especialmente en presencia de atípicos y datos contaminados.

  • English

    In this study, robust Brown-Forsythe and robust Modified Brown-Forsythe ANOVA tests are proposed to take into consideration heteroscedastic and non-normality data sets with outliers. The non-normal data is assumed to be a two parameters Weibull distribution. Robust proposed tests are obtained by using robust mean and variance estimators based on median/MAD and median/Qn methods instead of maximum likelihood. The behaviors of the robust proposed and classical ANOVA tests are examined by simulation study. The results shows that the proposed robust tests have good performance especially in the presence of heteroscedasticity and contamination.

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