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EnglishThis paper deals with the Bayesian analysis of graphical models of marginal independence for three way contingency tables. Each marginal independence model corresponds to a particular factorization of the cell probabilities and a conjugate analysis based on Dirichlet prior can be performed. We illustrate a comprehensive Bayesian analysis of such models, involving suitable choices of prior parameters, estimation, model determination, as well as the allied computational issues. The posterior distributions of the marginal log-linear parameters is indirectly obtained using simple Monte Carlo schemes. The methodology is illustrated using two real data sets.
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| Titolo: | Bayesian Analysis of Marginal Log-Linear Graphical Models for Three Way Contingency Tables | |
| Autori: | ||
| Data di pubblicazione: | 2012 | |
| Serie: | ||
| Abstract: | This paper deals with the Bayesian analysis of graphical models of marginal independence for three way contingency tables. Each marginal independence model corresponds to a particular factorization of the cell probabilities and a conjugate analysis based on Dirichlet prior can be performed. We illustrate a comprehensive Bayesian analysis of such models, involving suitable choices of prior parameters, estimation, model determination, as well as the allied computational issues. The posterior distributions of the marginal log-linear parameters is indirectly obtained using simple Monte Carlo schemes. The methodology is illustrated using two real data sets. | |
| Handle: | http://hdl.handle.net/11571/140255 | |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
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