The log-linear model with a generalized gamma distribution for the error: A Bayesian approach |
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| Institution: | 1. ITAM. Department of Political Sciennce. Río Hondo 1, Altavista, Álvaro Obregón, 01080 Ciudad de México, CDMX;1. Department of Psychiatry, University of Lausanne, Switzerland;2. Department of Economics and Management, University of Pisa, Italy;3. Department of Political Science, University of Pisa, Italy;1. Graduate School of Social Sciences, Chiba University, 1-33, Yayoi-cho, Inage-ku, 2638522, Chiba, Japan;2. School of Commerce, Meiji University, 1-1, Kanda Surugadai, Chiyoda-ku, 1018301, Tokyo, Japan |
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| Abstract: | Considering a log-linear model with one covariate and a generalized gamma distribution for the error, we find the posterior densities for the parameters of interest. Since many standard survival distributions are particular cases of the generalized gamma model, the proposed bayesian method is very useful to discriminate between possible models to be used in the data analysis. The Laplace approximation for integrals (see Tierney and Kadane, 1984) is used to find the posterior distributions of the parameters involved when they cannot be obtained explicitly. |
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