Consistent high-dimensional Bayesian variable selection via penalized credible regions.

@article{Bondell2012ConsistentHB,
  title={Consistent high-dimensional Bayesian variable selection via penalized credible regions.},
  author={Howard D. Bondell and Brian J. Reich},
  journal={Journal of the American Statistical Association},
  year={2012},
  volume={107 500},
  pages={
          1610-1624
        }
}
For high-dimensional data, particularly when the number of predictors greatly exceeds the sample size, selection of relevant predictors for regression is a challenging problem. Methods such as sure screening, forward selection, or penalized regressions are commonly used. Bayesian variable selection methods place prior distributions on the parameters along with a prior over model space, or equivalently, a mixture prior on the parameters having mass at zero. Since exhaustive enumeration is not… CONTINUE READING

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