Uma abordagem clássica e bayesiana para os modelos de Gompertz e de Richards heteroscedásticos

Abstract

This work presents a classical and a Bayesian approaches to two sigmoidal grownth curves, the Gompertz and the Richards models. We consider the homoscedastic assumption and a multiplicative heteroscedastic structure. For the classical approach we use the maximum likelihood method and for bayesian approach we consider non-informative priors. The posterioris summaries were obtained by the use of the Metropolis-Hastings algorithm. The illustration of both approaches is made using a simulated and a real data set.