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Title: | Bayesian inferences for the Birnbaum-Saunders Special-Case distribution |
Other Titles: | Inferência bayesiana na distribuição Birnbaum-Saunders Caso-Especial |
Authors: | Nakamura, Luiz Ricardo Leandro, Roseli Aparecida Villegas, Cristian |
Keywords: | Generalized Birnbaum-Saunders distributions Markov chain Monte Carlo Metropolis-Hastings algorithm Random number generator Distribuições Birnbaum-Saunders generalizadas Monte Carlo via cadeias de Markov Algoritmo Metropolis-Hastings Gerador de números aleatórios |
Issue Date: | 1-Aug-2017 |
Publisher: | Universidade Federal de Lavras |
Citation: | NAKAMURA, L. R.; LEANDRO, R. A.; VILLEGAS, C. Bayesian inferences for the Birnbaum-Saunders Special-Case distribution. Revista Brasileira de Biometria, Lavras, v. 34, n. 2, p. 365-378, jun. 2016. |
Abstract: | 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 |
Appears in Collections: | Revista Brasileira de Biometria |
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File | Description | Size | Format | |
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ARTIGO_Bayesian inferences for the Birnbaum-Saunders Special-Case distribution.pdf | 312,05 kB | Adobe PDF | View/Open |
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