Departamento de Estadísticas y Ciencia de datos

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http://repositorioabierto.uantof.cl/handle/uantof/220

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Examinando Departamento de Estadísticas y Ciencia de datos por Autor "Gallardo, Diego I."

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  • Miniatura
    Ítem
    An Extension of the Akash Distribution: Properties, Inference and Application
    (MDPI, 2024) Gómez, Yolanda M.; Firinguetti Limone, Luis; Gallardo, Diego I.; Gómez, Héctor W.
    In this article we introduce an extension of the Akash distribution. We use the slash methodology to make the kurtosis of the Akash distribution more flexible. We study the general probability density function of this new model, some properties, moments, skewness and kurtosis coefficients. Statistical inference is performed using the methods of moments and maximum likelihood via the EM algorithm. A simulation study is carried out to observe the behavior of the maximum likelihood estimator. An application to a real data set with high kurtosis is considered, where it is shown that the new distribution fits better than other extensions of the Akash distribution.
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    Ítem
    Reparameterized Scale Mixture of Rayleigh DistributionRegression Models with Varying Precision
    (MDPI, 2024) Rivera, Pilar A.; Gallardo, Diego I.; Venegas, Osvaldo; Gómez Déniz, Emilio; Gómez, Héctor W.
    In this paper, we introduce a new parameterization for the scale mixture of the Rayleigh distribution, which uses a mean linear regression model indexed by mean and precision parameters to model asymmetric positive real data. To test the goodness of fit, we introduce two residuals for the new model. A Monte Carlo simulation study is performed to evaluate the parameter estimation of the proposed model. We compare our proposed model with existing alternatives and illustrate its advantages and usefulness using Gilgais data in R software version 4.2.3 with the gamlss package