Adaptive prior weighting in generalized regression.

  title={Adaptive prior weighting in generalized regression.},
  author={Leonhard Held and Rafael Sauter},
  volume={73 1},
The prior distribution is a key ingredient in Bayesian inference. Prior information on regression coefficients may come from different sources and may or may not be in conflict with the observed data. Various methods have been proposed to quantify a potential prior-data conflict, such as Box's p-value. However, there are no clear recommendations how to react to possible prior-data conflict in generalized regression models. To address this deficiency, we propose to adaptively weight a… CONTINUE READING
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