Package: SMLE
Title: Joint Feature Screening via Sparse MLE
Version: 2.1-1
Maintainer: Qianxiang Zang <qzang023@uottawa.ca>
Description: 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.
License: GPL-3
Depends: R(>= 4.0.0)
Imports: glmnet, matrixcalc, mvnfast
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Author: Qianxiang Zang [aut, cre],
  Chen Xu [aut],
  Kelly Burkett [aut],
Repository: CRAN
Packaged: 2024-02-12 21:39:02 UTC; mac
Date/Publication: 2024-02-12 21:50:03 UTC
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Built: R 4.2.3; ; 2024-04-24 01:53:57 UTC; windows
