Slope heuristics for variable selection and clustering via Gaussian mixtures

@inproceedings{Maugis2008SlopeHF,
  title={Slope heuristics for variable selection and clustering via Gaussian mixtures},
  author={Cathy Maugis and Bertrand Michel},
  year={2008}
}
Specific Gaussian mixtures are considered to solve simultaneously variable selection and clustering problems. A penalized likelihood criterion is proposed in Maugis and Michel (2008) to choose the number of mixture components and the relevant variable subset. This criterion is depending on unknown constants to be approximated in practical situations. A “slope heuristics” method is proposed and experimented to deal with this practical problem in this context. Numerical experiments on simulated… CONTINUE READING