One-step sparse estimates in nonconcave penalized likelihood models
One-step sparse estimates in nonconcave penalized likelihood models
Fan and Li propose a family of variable selection methods via penalized likelihood using concave penalty functions. The nonconcave penalized likelihood estimators enjoy the oracle properties, but maximizing the penalized likelihood function is computationally challenging, because the objective function is nondifferentiable and nonconcave. In this article, we propose a new …