A note on automatic variable selection using smooth-threshold estimating equations
A note on automatic variable selection using smooth-threshold estimating equations
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DOI：
10.1093/biomet/asp060
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发表时间：
2009-12-01
期刊：
影响因子：
2.7
通讯作者：
Ueki, Masao
中科院分区：
文献类型：
--
作者：
Ueki, Masao
本文提出了一种平滑阈值估计方程，通过将无关参数置零，可以自动剔除无关参数。由此得到的估计量在Fan & Li（2001）的意义下具有预言性质，即使在违背Wang & Leng（2007）的协方差假设的估计量中，例如Buckley-James估计量。此外，估计器可以得到没有解决凸优化问题。一个bic型的标准，调谐参数的选择也提出了。结果表明，该准则实现了一致的模型选择。数值研究证实了该方法的性能。
This paper develops smooth-threshold estimating equations that can automatically eliminate irrelevant parameters by setting them as zero. The resulting estimator enjoys the oracle property in the sense of Fan & Li (2001), even in estimators for which the covariance assumption of Wang & Leng (2007) is violated, such as the Buckley-James estimator. Furthermore, the estimator can be obtained without solving a convex optimization problem. A bic-type criterion for tuning parameter selection is also proposed. It is shown that the criterion achieves consistent model selection. A numerical study confirms the performance of the method.