Bayesian Input Variable Selection Using Posterior Probabilities and Expected

  title={Bayesian Input Variable Selection Using Posterior Probabilities and Expected},
  author={Aki Vehtari},
We consider the input variable selection in complex Bayesia n h erarchical models. Our goal is to find a model with the smallest number of input variables havin g statistically or practically at least the same expected utility as the full model with all the availabl e inputs. A good estimate for the expected utility can be computed using cross-validation predictive densities. In the case of input selection and a large number of input combinations, the computation of the cross-validation… CONTINUE READING
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