Reparameterized Scale Mixture of Rayleigh DistributionRegression Models with Varying Precision
| dc.contributor.author | Pilar A. Rivera | |
| dc.contributor.author | Diego I. Gallardo | |
| dc.contributor.author | Osvaldo Venegas | |
| dc.contributor.author | Emilio Gómez Déniz | |
| dc.contributor.author | Héctor W. Gómez | |
| dc.date.accessioned | 2026-04-06T14:03:49Z | |
| dc.date.available | 2026-04-06T14:03:49Z | |
| dc.date.issued | 2024 | |
| dc.description.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 | |
| dc.description.sponsorship | Semillero UA-2024 | |
| dc.identifier.doi | 10.3390/math12131982 | |
| dc.identifier.issn | 22277390 | |
| dc.identifier.uri | https://repositorioabierto.uantof.cl/handle/uantof/681 | |
| dc.language.iso | en | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.source | Mathematics | |
| dc.title | Reparameterized Scale Mixture of Rayleigh DistributionRegression Models with Varying Precision | |
| dc.type | Article | |
| oaire.citation.volume | 12 | |
| organization.identifier.ror | Universidad de Antofagasta | |
| uantof.identificator.department | Departamento de Estadística y Ciencia de Datos | |
| uantof.identificator.faculty | Facultad de Ciencias Básicas |