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Open AccessArticle

Skewness of Maximum Likelihood Estimators in the Weibull Censored Data

1
Department of Statistics, Institute of Exact Sciences, Federal University of Juiz de Fora, Juiz de Fora 36000-000, Brazil
2
Departamento de Matemática, Facultad de Ingeniería, Universidad de Atacama, Copiapó 1530000, Chile
3
Departamento de Matemáticas, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(11), 1351; https://doi.org/10.3390/sym11111351
Received: 29 September 2019 / Revised: 17 October 2019 / Accepted: 21 October 2019 / Published: 1 November 2019
In this paper, we obtain a matrix formula of order n 1 / 2 , where n is the sample size, for the skewness coefficient of the distribution of the maximum likelihood estimators in the Weibull censored data. The present result is a nice approach to verify if the assumption of the normality of the regression parameter distribution is satisfied. Also, the expression derived is simple, as one only has to define a few matrices. We conduct an extensive Monte Carlo study to illustrate the behavior of the skewness coefficient and we apply it in two real datasets. View Full-Text
Keywords: maximum likelihood estimates; type I and II censoring; skewness coefficient; Weibull censored data maximum likelihood estimates; type I and II censoring; skewness coefficient; Weibull censored data
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Magalhães, T.M.; Gallardo, D.I.; Gómez, H.W. Skewness of Maximum Likelihood Estimators in the Weibull Censored Data. Symmetry 2019, 11, 1351.

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