Reparameterized Scale Mixture of Rayleigh Distribution Regression Models with Varying Precision

Rivera P.A.; Gallardo D.I.; Venegas O.; Gómez-Déniz, E; Gomez H.W.

Keywords: maximum likelihood estimator, residuals, regression models, scale mixture of Rayleigh distribution

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.

Más información

Título según WOS: Reparameterized Scale Mixture of Rayleigh Distribution Regression Models with Varying Precision
Volumen: 12
Número: 13
Fecha de publicación: 2024
Idioma: English
DOI:

10.3390/math12131982

Notas: ISI