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A novel fully automatic Bayesian procedure for variable selection in normal regression model is proposed. The procedure uses the posterior probabilities of the models to drive a stochastic search. The posterior probabilities are computed using intrinsic priors, which can be considered default priors for model selection problems. That is, they are derived(More)
A condition needed for testing nested hypotheses from a Bayesian viewpoint is that the prior for the alternative model concentrates mass around the smaller, or null, model. For testing independence in contingency tables, the intrinsic priors satisfy this requirement. Further, the degree of concentration of the priors is controlled by a discrete parameter m,(More)
It has long been known that for the comparison of pairwise nested models, a decision based on the Bayes factor produces a consistent model selector (in the frequentist sense). Here we go beyond the 1 usual consistency for nested pairwise models, and show that for a wide class of prior distributions, including intrinsic priors, the corresponding Bayesian(More)
A retrospective review is presented of neurologic complications in our first 143 consecutive adult patients (208 liver transplants in 143 adults and 18 children) undergoing liver transplantation. Nineteen (13.2%) of the 143 patients developed neurologic complications in the postoperative period. Immunosuppression was initiated intraoperatively with steroids(More)
A cross-sectional epidemiological study of two communities in Guatemala, El Jocote and Quesada, was conducted to determine the prevalence of epilepsy and epileptic seizures. An initial screening questionnaire was applied to detect individuals who had possibly suffered seizures in the past. These individuals were then examined more thoroughly by a(More)
In the objective Bayesian approach to variable selection in regression a crucial point is the encompassing of the underlying nonnested linear models. Once the models have been encompassed one can define objective priors for the multiple testing problem involved in the variable selection problem. There are two natural ways of encompassing: one way is to(More)
Clustering is an important and challenging statistical problem for which there is an extensive literature. Modeling approaches include mixture models and product partition models. Here we develop a product partition model and a model selection procedure based on Bayes factors from intrinsic priors. We also find that the choice of the prior on model space is(More)
Palabras clave: Ecografía cerebral. Tomografía axial computarizada. Resonancia magnética. Parálisis cere-bral. Summary.—This is a retrospective study which aims to determine the correlation between the clinical findings and the neuroradiological brain findings of the patients seen in the Cerebral Palsy Unit (CP). To do so, the first visits made between June(More)