Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/13967
Title: BAYESIAN INFERENCES FOR THE BIRNBAUM-SAUNDERS SPECIAL-CASE DISTRIBUTION
Issue Date: 1-Aug-2017
Publisher: Editora UFLA - Universidade Federal de Lavras - UFLA
Description: In this paper, we discuss the estimation of the Birnbaum-Saunders Special-Case (BS-SC) distribution through the Bayesian approach considering its parameters independents, assuming gamma priors for both of them. As the full posterior conditionals do not have closed forms we use the Metropolis-Hastings algorithm to generate samples from the joint posterior distribution. We present a simulation study proposing the Markov chain Monte Carlo (MCMC) method as a random number generator, considering the cases where the BS-SC distribution has symmetric and asymmetric shapes. An application related to ozone concentration is presented in this paper using the described methodology.
URI: http://repositorio.ufla.br/jspui/handle/1/13967
Other Identifiers: http://www.biometria.ufla.br/index.php/BBJ/article/view/146
Appears in Collections:Revista Brasileira de Biometria

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