ar X iv : 0 90 3 . 25 15 v 1 [ m at h . ST ] 1 3 M ar 2 00 9 Adaptive Lasso for High Dimensional Regression and Gaussian Graphical Modeling
نویسندگان
چکیده
We show that the two-stage adaptive Lasso procedure (Zou, 2006) is consistent for high-dimensional model selection in linear and Gaussian graphical models. Our conditions for consistency cover more general situations than those accomplished in previous work: we prove that restricted eigenvalue conditions (Bickel et al., 2008) are also sufficient for sparse structure estimation.
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