Publicación:
PARAMETRIC QUANTILE REGRESSION MODELS FOR FITTING DOUBLE BOUNDED RESPONSE WITH APPLICATION TO COVID-19 MORTALITY RATE DATA

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dc.creatorCHRISTIAN ELOY CAAMAÑO CARRILLO
dc.date2022
dc.date.accessioned2025-01-10T15:29:22Z
dc.date.available2025-01-10T15:29:22Z
dc.date.issued2022
dc.description.abstractIN THIS PAPER, WE DEVELOP TWO FULLY PARAMETRIC QUANTILE REGRESSION MODELS, BASED ON THE POWER JOHNSON SB DISTRIBUTION FOR MODELING UNIT INTERVAL RESPONSE IN DIFFERENT QUANTILES. IN PARTICULAR, THE CONDITIONAL DISTRIBUTION IS MODELED BY THE POWER JOHNSON SB DISTRIBUTION. THE MAXIMUM LIKELIHOOD (ML) ESTIMATION METHOD IS EMPLOYED TO ESTIMATE THE MODEL PARAMETERS. SIMULATION STUDIES ARE CONDUCTED TO EVALUATE THE PERFORMANCE OF THE ML ESTIMATORS IN FINITE SAMPLES. FURTHERMORE, WE DISCUSS INFLUENCE DIAGNOSTIC TOOLS AND RESIDUALS. THE EFFECTIVENESS OF OUR PROPOSALS IS ILLUSTRATED WITH A DATA SET OF THE MORTALITY RATE OF COVID-19 IN DIFFERENT COUNTRIES. THE RESULTS OF OUR MODELS WITH THIS DATA SET SHOW THE POTENTIAL OF USING THE NEW METHODOLOGY. THUS, WE CONCLUDE THAT THE RESULTS ARE FAVORABLE TO THE USE OF PROPOSED QUANTILE REGRESSION MODELS FOR FITTING DOUBLE BOUNDED DATA.
dc.formatapplication/pdf
dc.identifier.doi10.3390/math10132249
dc.identifier.issn2227-7390
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/12256
dc.languagespa
dc.publisherMATHEMATICS
dc.relation.uri10.3390/math10132249
dc.rightsPUBLICADA
dc.titlePARAMETRIC QUANTILE REGRESSION MODELS FOR FITTING DOUBLE BOUNDED RESPONSE WITH APPLICATION TO COVID-19 MORTALITY RATE DATA
dc.title.alternativeMODELOS DE REGRESIÓN CUANTIL PARAMÉTRICA PARA AJUSTAR LA RESPUESTA DE DOBLE LÍMITE CON LA APLICACIÓN A LOS DATOS DE LA TASA DE MORTALIDAD POR COVID-19
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE ESTADISTICA
ubb.SedeCONCEPCIÓN
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