A beta inflated mean regression model for fractional response variables

Cristian L. Bayes, Luis Valdivieso

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

ABSTRACT: This article proposes a new regression model for a dependent fractional random variable on the interval (Formula presented.) 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.

Original languageEnglish
Pages (from-to)1814-1830
Number of pages17
JournalJournal of Applied Statistics
Volume43
Issue number10
DOIs
StatePublished - 26 Jul 2016

Keywords

  • Fractional data
  • beta regression
  • maximum likelihood estimation

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