Reparameterized Scale Mixture of Rayleigh Distribution Regression Models with Varying Precision
Reparameterized Scale Mixture of Rayleigh Distribution Regression Models with Varying Precision
Authors
Rivera, Pilar A.
Gallardo, Diego I.
Venegas, Osvaldo
Gomez Deniz, Emilio
Gomez, Hector W.
Gallardo, Diego I.
Venegas, Osvaldo
Gomez Deniz, Emilio
Gomez, Hector W.
Profesor GuĆa
Authors
Date
Datos de publicaciĆ³n:
10.3390/math12131982
MATHEMATICS,Vol.12,2024
MATHEMATICS,Vol.12,2024
Tipo de recurso
Article
Keywords
Materia geogrƔfica
Collections
Abstract
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.