若 \hat{\beta} 是root n consistent estimator,可取 \hat{w}=1/|\hat{\beta}|^\gamma,\gamma>0 。在稀疏模型中, \gamma 可取1,这方面的研究可以看下《Adaptive Lasso For Sparse High-Dimensional Regression Models》。 2. Dantzig Selector Dantzig Selector是Emmanuel Cansed 和 Terence Tao于2007年在...
Adaptive Lasso, introduced by Hui Zou in 2006, offers an improvement to Lasso estimation. The Lasso method minimizes squared error to find parameter estimates, but can sometimes fail in variable selection. The Adaptive Lasso introduces a weighting scheme to Lasso's penalty term. This w...
本文提出一种基于AdaptiveLasso的2阶段全基因组关联分析方法(two-stage Adaptive...展开更多 As mainstream methods for genome-wide association analysis,mixed linear model methods have been widely used.However,the existing methods still have the problem of low detection power.In this study,a two-stage ...