A beta inflated mean regression model for fractional response variables. Issue 10 (26th July 2016)

• Record Type: Journal Article
• Authors: Bayes, Cristian L.; Valdivieso, Luis
• Is Part Of: Journal of applied statistics. Volume 43:Issue 10(2016)
• Page Start: 1814
• Page End: 1830
• Publication Date: 2016-07-26
• Subjects: Fractional data -- beta regression -- maximum likelihood estimation; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2015.1120711
• Languages: English
• ISSNs: 0266-4763

Abstract

ABSTRACT: This article proposes a new regression model for a dependent fractional random variable on the interval [ 0, 1 ] that takes with positive probability the extreme values 0 or 1. Our model relates the expected value of this variable with a linear predictor through a special parametrization that let the parameters free in the parameter space. A simulation-based study and an application to capital structure choices were conducted to analyze the performance of the likelihood estimators in the model. The results show not only accurate estimations and a better fit than other traditional models but also a more straightforward and clear way to estimate the effects of a set of covariates over the mean of a fractional response.