SMLE
Joint Feature Screening via Sparse MLE
Feature screening is a powerful tool in processing ultrahigh dimensional data. It attempts to screen out most irrelevant features in preparation for a more elaborate analysis. Xu and Chen (2014)<doi:10.1080/01621459.2013.879531> proposed an effective screening method SMLE, which naturally incorporates the joint effects among features in the screening process. This package provides an efficient implementation of SMLE-screening for high-dimensional linear, logistic, and Poisson models. The package also provides a function for conducting accurate post-screening feature selection based on an iterative hard-thresholding procedure and a user-specified selection criterion. Zang, Xu, and Burkett (2025)<doi:10.18637/jss.v115.i08>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.2-3 |
rolling linux/jammy R-4.5 | SMLE_2.2-3.tar.gz |
3.1 MiB |
2.2-3 |
rolling linux/noble R-4.5 | SMLE_2.2-3.tar.gz |
3.1 MiB |
2.2-3 |
rolling source/ R- | SMLE_2.2-3.tar.gz |
1.9 MiB |
2.2-3 |
latest linux/jammy R-4.5 | SMLE_2.2-3.tar.gz |
3.1 MiB |
2.2-3 |
latest linux/noble R-4.5 | SMLE_2.2-3.tar.gz |
3.1 MiB |
2.2-3 |
latest source/ R- | SMLE_2.2-3.tar.gz |
1.9 MiB |
2.2-3 |
2026-04-26 source/ R- | SMLE_2.2-3.tar.gz |
1.9 MiB |
2.2-3 |
2026-04-23 source/ R- | SMLE_2.2-3.tar.gz |
1.9 MiB |
2.2-3 |
2026-04-09 windows/windows R-4.5 | SMLE_2.2-3.zip |
3.1 MiB |
2.2-2 |
2025-04-20 source/ R- | SMLE_2.2-2.tar.gz |
1.9 MiB |