Consistency of objective Bayes factors for nonnested linea r models and increasing model dimension

@inproceedings{Gir2010ConsistencyOO,
  title={Consistency of objective Bayes factors for nonnested linea r models and increasing model dimension},
  author={F. Javier Gir and Elı́as Moreno and George Casella and M. L. Martı́nez},
  year={2010}
}
Casella et al. [2, (2009)] proved that, under very general co nditions, for normal linear models the Bayes factor for a wide class of prior distributions, inc luding the intrinsic priors, is consistent when the number of parameters does not grow with the sample size n. The special attention paid to the intrinsic priors is due to the fact that they are nonsubjective priors, and thus accessible priors for complex models. The case where the number of parameters of nested models grow asO(nα) for… CONTINUE READING
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