Regularization of Case-Specific Parameters for Robustness and Efficiency

@inproceedings{Lee2007RegularizationOC,
  title={Regularization of Case-Specific Parameters for Robustness and Efficiency},
  author={Yoonkyung Lee and Steven N. MacEachern and Yoonsuh Jung},
  year={2007}
}
Regularization methods allow one to handle a variety of inferential problems where there are more covariates than cases. This allows one to consider a potentially enormous number of covariates for a problem. We exploit the power of these techniques, supersaturating models by augmenting the “natural” covariates in the problem with an additional indicator for each case in the data set. We attach a penalty term for these case-specific indicators which is designed to produce a desired effect. For… CONTINUE READING