NETWORK EXPLORATION VIA THE ADAPTIVE LASSO AND SCAD PENALTIES.

@article{Fan2009NETWORKEV,
  title={NETWORK EXPLORATION VIA THE ADAPTIVE LASSO AND SCAD PENALTIES.},
  author={Jianqing Fan and Yang Feng and Yichao Wu},
  journal={The annals of applied statistics},
  year={2009},
  volume={3 2},
  pages={
          521-541
        }
}
Graphical models are frequently used to explore networks, such as genetic networks, among a set of variables. This is usually carried out via exploring the sparsity of the precision matrix of the variables under consideration. Penalized likelihood methods are often used in such explorations. Yet, positive-definiteness constraints of precision matrices make the optimization problem challenging. We introduce non-concave penalties and the adaptive LASSO penalty to attenuate the bias problem in the… 

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