This paper introduces a new four-parameter lifetime model called the odd log-logistic Dagum distribution. The new model has the advantage of being capable of modeling various shapes of aging and failure criteria. We derive some structural properties of the model odd log-logistic Dagum such as order statistics and incomplete moments. The maximum likelihood method is used to estimate the model parameters. Simulation results to assess the performance of the maximum likelihood estimation are discussed. We prove empirically the importance and exibility of the new model in modeling real data. Este artículo introduce un nuevo modelo de sobrevida de cuatro paráme-tros llamado la distribución Odd Log-Logistica de Dagum. El nuevo modelo tiene la ventaja de ser capaz de modelar varias formas de envejecimiento y criterios de falla. Derivamos propiedades estructurales del modelo Odd Log-Logistica de Dagum tales como estadísticos de orden y momentos incompletos. El método de máxima verosimilitud es usado para estimar los parámetros del modelo. Se discuten resultados de algunas simulaciones, las cuales permitieron establecer la eciencia del método de máxima verosimilitud. Probamos empíricamente la importancia y exibilidad del nuevo modelo a través de un ejemplo en datos reales.Palabras clave: distribución Dagum; familia Odd-Log-Logística; máxima verosimilitud; estadísticas de orden.
A flexible ranked set sampling scheme including some various existing sampling methods is proposed. This scheme may be used to minimize the error of ranking and the cost of sampling. Based on the data obtained from this scheme, the maximum likelihood estimation as well as the Fisher information are studied for the scale family of distributions. The existence and uniqueness of the maximum likelihood estimator of the scale parameter of the exponential and normal distributions are investigated. Moreover, the optimal scheme is derived via simulation and numerical computations.
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