The weighted beta regression for modeling bounded data
Conference
65th ISI World Statistics Congress 2025
Format: IPS Abstract - WSC 2025
Tuesday 7 October 2 p.m. - 3:40 p.m. (Europe/Amsterdam)
Abstract
A two-parameter weighted beta distribution is introduced for modeling bounded data, which
has many similarities to the beta distribution. We propose a class of regression models where the
response is weighted beta distributed and the two shape parameters that index weighted the beta
distribution are related to covariates and regression parameters. The proposed regression model
is a natural strong competitor of the beta regression model. We study mathematical and statistical
properties of the distribution and we provide a useful interpretation of the parameters. The
maximum likelihood method is used for estimating the model parameters. Simulation studies are
conducted to investigate the performance of the maximum likelihood estimators and the asymptotic
confidence intervals of the parameters. An application of the proposed regression model to
real bounded data is presented.