Publicación:
PARAMETRIC QUANTILE BETA REGRESSION MODEL

Vista sencilla de ítem
dc.creatorDIEGO IGNACIO GALLARDO MATELUNA
dc.date2024
dc.date.accessioned2025-01-10T15:46:18Z
dc.date.available2025-01-10T15:46:18Z
dc.date.issued2024
dc.description.abstractIN THIS PAPER, WE DEVELOP A FULLY PARAMETRIC QUANTILE REGRESSION MODEL BASED ON THE GENERALISED THREE-PARAMETER BETA (GB3) DISTRIBUTION. BETA REGRESSION MODELS ARE PRIMARILY USED TO MODEL RATES AND PROPORTIONS. HOWEVER, THESE MODELS ARE USUALLY SPECIFIED IN TERMS OF A CONDITIONAL MEAN. THEREFORE, THEY MAY BE INADEQUATE IF THE OBSERVED RESPONSE VARIABLE FOLLOWS AN ASYMMETRICAL DIS- TRIBUTION. IN ADDITION, BETA REGRESSION MODELS DO NOT CONSIDER THE EFFECT OF THE COVARIATES ACROSS THE SPECTRUM OF THE DEPENDENT VARIABLE, WHICH IS POSSIBLE THROUGH THE CONDITIONAL QUANTILE APPROACH. IN ORDER TO INTRODUCE THE PROPOSED GB3 REGRESSION MODEL, WE FIRST REPARAMETERISE THE GB3 DISTRIBUTION BY INSERTING A QUANTILE PARAMETER, AND THEN WE DEVELOP THE NEW PROPOSED QUANTILE MODEL. WE ALSO PROPOSE A SIMPLE INTERPRETATION OF THE PREDICTOR?RESPONSE RELATIONSHIP IN TERMS OF PERCENTAGE INCREASES/DECREASES OF THE QUANTILE. A MONTE CARLO STUDY IS CARRIED OUT FOR EVALUATING THE PERFORMANCE OF THE MAXIMUM LIKELIHOOD ESTIMATES AND THE CHOICE OF THE LINK FUNCTIONS. FINALLY, A REAL COVID-19 DATASET FROM CHILE IS ANALYSED AND DISCUSSED TO ILLUSTRATE THE PROPOSED APPROACH.
dc.formatapplication/pdf
dc.identifier.doi10.1111/insr.12564
dc.identifier.issn1751-5823
dc.identifier.issn0306-7734
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/13581
dc.languagespa
dc.publisherINTERNATIONAL STATISTICAL REVIEW
dc.relation.uri10.1111/insr.12564
dc.rightsPUBLICADA
dc.subjectparametric quantile regression.
dc.subjectGB3 distribution
dc.subjectCOVID-19
dc.subjectcase fatality rate
dc.subjectBeta distribution
dc.titlePARAMETRIC QUANTILE BETA REGRESSION MODEL
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE ESTADISTICA
ubb.SedeCONCEPCIÓN
Archivos
Colecciones
Artículos científicos