A permutation approach for selecting the penalty parameter in penalized model selection.

@article{Sabourin2014APA,
  title={A permutation approach for selecting the penalty parameter in penalized model selection.},
  author={Jeremy A. Sabourin and William Valdar and Andrew B. Nobel},
  journal={Biometrics},
  year={2014},
  volume={71 4},
  pages={
          1185-94
        }
}
  • Jeremy A. Sabourin, William Valdar, Andrew B. Nobel
  • Published in Biometrics 2014
  • Computer Science, Medicine, Mathematics
  • We describe a simple, computationally efficient, permutation-based procedure for selecting the penalty parameter in LASSO-penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study… CONTINUE READING

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