Risk and resampling under model uncertainty

  title={Risk and resampling under model uncertainty},
  author={Snigdhansu Chatterjee and Nitai D. Mukhopadhyay},
In statistical exercises where there are several candidate models, the traditional approach is to select one model using some data driven criterion and use that model for estimation, testing and other purposes, ignoring the variability of the model selection process. We discuss some problems associated with this approach. An alternative scheme is to use a model-averaged estimator, that is, a weighted average of estimators obtained under different models, as an estimator of a parameter. We show… CONTINUE READING

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