Prioris para modelos probabilísticos discretos em ciências agrárias

• Autor(a) principal: SARAIVA, Cristiane Almeida
• Data de Publicação: 2007
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFRPE
• Texto Completo: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5087
• topic: Modelo probabilístico; Estatística Bayesiana; Produção de ovos; Probabilistic model; Bayesian statistics; Egg production; CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA

With the propose to choose priors more fited for discrete data, we study technics for determination of priors just as Laplace’s Methods, Jeffreys’s Methods and Haldane’s Methods which are conjugated prior. We take a sample of ten grange among the fifty three ones existent of the Pernambuco’s State to estimate the probability of commercial egg (big type). We suppose that the distribution from the sample data is binomial and we use the methods quoted above. The software used for that was the package Winbugs 1.4 where we compute the average, standard deviation, 95% credible interval and their amplitude. For each one of the methods it was observed that 20.000 iterations were sufficient since the balance of the chain already had established with 12.500 iterations. The estimated parameter p=0,664 was obtained by the Laplace’s Method, Jeffreys’s Method and Haldane’s Method.