caa a22 4500 477092209 CHVBK 20180405111518.0 cr unu---uuuuu 170330e19960401xx s 000 0 eng 10.1007/BF02589585 doi (NATIONALLICENCE)springer-10.1007/BF02589585 Global prior distributions for the analysis of discrete graphical models [Elektronische Daten] [Paolo Giudici, Claudia Tarantola] Summary: We propose a new class of prior distributions for the analysis of discrete graphical models. Such a class, obtained following a conditional approach, generalizes the hyper Dirichlet distributions of Dawid and Lauritzen (1993), since it can be extended to non decomposable graphical models. The two classes are compared in terms of model selection, with an application to a medical data-set illustrating the performance of the two resulting procedures. The proposed class turns out to select simpler, more par-simonious structures. Società Italiana di Statistica, 1996 Bayesian model selection nationallicence Contingency tables nationallicence Dirichlet distribution nationallicence Hyper Markov distributions nationallicence Giudici Paolo Università di Pavia, Pavia, Italy aut Tarantola Claudia Università di Trento, Trento, Italy aut Journal of the Italian Statistical Society Springer-Verlag 5/1(1996-04-01), 129-147 1121-9130 5:1<129 1996 5 10260 https://doi.org/10.1007/BF02589585 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF02589585 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Giudici Paolo Università di Pavia, Pavia, Italy aut NATIONALLICENCE 700 1- Tarantola Claudia Università di Trento, Trento, Italy aut NATIONALLICENCE 773 0- Journal of the Italian Statistical Society Springer-Verlag 5/1(1996-04-01), 129-147 1121-9130 5:1<129 1996 5 10260 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer