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Revista Colombiana de Estadística
Print version ISSN 0120-1751
Rev.Colomb.Estad. vol.44 no.1 Bogotá Jan./June 2021 Epub Feb 26, 2021
https://doi.org/10.15446/rce.v44n1.86566
Original articles of research
A Reparameterized Weighted Lindley Distribution: Properties, Estimation and Applications
Una distribución de Lindley ponderada reparametrizada: propiedades, estimación y aplicaciones
1Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, Brazil
2Departamento de Estatística, Instituto de Matemática e Estatística, Universidade Federal da Bahia, Salvador, Brazil
3Departamento de Estatística, Centro de Ciências Exatas e de Tecnologia, Universidade Federal de São Carlos, São Carlos, Brazil
In this paper, we discuss several mathematical properties and estimation methods for a reparameterized version of the weighted Lindley (RWL) distribution. The RWL distribution can be particularly useful for modeling reliability (survival) data with bathtub-shaped or increasing hazard rate function. The inferential procedure to obtain the parameter estimates is conducted via the maximum likelihood approach considering random right-censoring. Extensive numerical simulations are carried out to investigate and evaluate the performance of the proposed estimation method. Finally, the potentiality of the RWL model is analyzed by employing two real data sets.
Key words: Lindley distribution; Monte Carlo simulation; Random right-censoring data; Weighted Lindley distribution
En este artículo, discutimos varias propiedades matemáticas y métodos de estimación para una versión reparametrizada de la distribución ponderada de Lindley (RWL). La distribución RWL puede ser particularmente útil para modelar datos de confiabilidad (supervivencia) con función de tasa de riesgo en forma de bañera o creciente. El procedimiento inferencial para obtener las estimaciones de los parámetros se realiza mediante el enfoque de máxima verosimilitud considerando la censura aleatoria a la derecha. Se realizan extensas simulaciones numéricas para investigar y evaluar el rendimiento del método de estimación propuesto. Finalmente, la utilidad del modelo RWL se analiza mediante el uso de dos conjuntos de datos reales.
Palabras clave: Datos censurados aleatorios a la derecha; Distribución de Lindley; Distribución ponderada de Lindley; Simulación Monte Carlo
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