sealasso: Standard Error Adjusted Adaptive Lasso
Standard error adjusted adaptive lasso (SEA-lasso) is a version of the adaptive lasso, which incorporates OLS standard error to the L1 penalty weight. This method is intended for variable selection under linear regression settings (n > p). This new weight assignment strategy is especially useful when the collinearity of the design matrix is a concern.
Version: |
0.1-3 |
Depends: |
R (≥ 2.9.1), lars |
Published: |
2022-04-22 |
Author: |
Wei Qian |
Maintainer: |
Wei Qian <weiqian at stat.umn.edu> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
no |
Materials: |
ChangeLog |
CRAN checks: |
sealasso results |
Documentation:
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