A bayesian approach to parameter estimation in simplex regression model: a comparison with beta regression

Abstract

Some variables are restricted to the open interval (0; 1) and several methodshave been developed to work with them under the scheme of the regressionanalysis. Most of research consider maximum likelihood methods andthe use of Beta or Simplex distributions.This paper presents the use of Bayesian techniques to estimate the parametersof the simplex regression supported on the implementation of somesimulations and a comparison with Beta regression. We consider both modelswith constant variance and models with