Assessment of two approximation methods for computing posterior model probabilities

@article{Boone2005AssessmentOT,
  title={Assessment of two approximation methods for computing posterior model probabilities},
  author={Edward L. Boone and Keying Ye and Eric P. Smith},
  journal={Computational Statistics & Data Analysis},
  year={2005},
  volume={48},
  pages={221-234}
}
Model selection is an important problem in statistical applications. Bayesian model averaging provides an alternative to classical model selection procedures and allows researchers to consider several models from which to draw inferences. In the multiple linear regression case, it is di4cult to compute exact posterior model probabilities required for Bayesian model averaging. To reduce the computational burden the Laplace approximation and an approximation based on the Bayesian information… CONTINUE READING
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