Majorization minimization by coordinate descent for concave penalized generalized linear models

@article{Jiang2014MajorizationMB,
  title={Majorization minimization by coordinate descent for concave penalized generalized linear models},
  author={Dingfeng Jiang and Jian Huang},
  journal={Statistics and computing},
  year={2014},
  volume={24 5},
  pages={871-883}
}
Recent studies have demonstrated theoretical attractiveness of a class of concave penalties in variable selection, including the smoothly clipped absolute deviation and minimax concave penalties. The computation of the concave penalized solutions in high-dimensional models, however, is a difficult task. We propose a majorization minimization by coordinate descent (MMCD) algorithm for computing the concave penalized solutions in generalized linear models. In contrast to the existing algorithms… CONTINUE READING