@article{ASSANE_PEREIRA_PEREIRA_2018, title={O PROCEDIMENTO FBST PARA DISCRIMINACÃO ENTRE AS DISTRIBUIÇÕES LOGNORMAL E WEIBULL}, volume={36}, url={https://biometria.ufla.br/index.php/BBJ/article/view/164}, DOI={10.28951/rbb.v36i1.164}, abstractNote={<p>Tests of separate families of hypotheses were initially considered by Cox&nbsp;(1961,1962). In this paper we examine the Fully Bayesian Signicance Test, FBST, for&nbsp;discriminating between the lognormal andWeibull models whose families of distributions&nbsp;are separate. Here, we analyze this problem in the context of linear mixture models. The&nbsp;FBST procedure is used for testing the hypotheses on the mixture weights in order to<br>calculate the evidence measure in favor of each model. In this work, the density functions&nbsp;of the mixture components are reparametrized in terms of the common parameters,&nbsp;the mean and the variance of the population, since the comparison between the&nbsp;models is based on the same dataset, that is, on the same population. In order to evaluate&nbsp;the performance of the proposed method, some numerical results based on simulations&nbsp;of sample points are given. In these simulations, the results of FBST are compared&nbsp;with those of the Cox test. Two application examples illustrating the procedures for&nbsp;uncensored data set are also presented.</p>}, number={1}, journal={Brazilian Journal of Biometrics}, author={ASSANE, Cachimo Combo and PEREIRA, Basílio de Bragança and PEREIRA, Carlos Alberto de Bragança}, year={2018}, month={Mar.}, pages={188–206} }