Quadratic approximation for nonconvex penalized estimations with a diverging number of parameters
We propose an approximated penalized estimator (APE) that covers various statistical models and nonconvex penalties including the smoothly clipped absolute deviation (SCAD) penalty (Fan and Li, 2001) as a special case. The APE achieves the oracle property with a diverging number of parameters which extends the results of Kwon et al. (2011). Several numerical studies confirm the theoretical results.
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Volume (Year): 82 (2012)
Issue (Month): 9 ()
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- Hansheng Wang & Bo Li & Chenlei Leng, 2009. "Shrinkage tuning parameter selection with a diverging number of parameters," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 671-683.
- Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
- Leng, Chenlei & Li, Bo, 2010. "Least squares approximation with a diverging number of parameters," Statistics & Probability Letters, Elsevier, vol. 80(3-4), pages 254-261, February.
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