Package: SMLE
Title: Joint Feature Screening via Sparse MLE
Version: 2.2-3
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. Zang, Xu, and Burkett (2025)<doi:10.18637/jss.v115.i08>.
License: GPL-3
Depends: R(>= 4.0.0)
Imports: glmnet, matrixcalc, mvnfast
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
NeedsCompilation: no
Author: Qianxiang Zang [aut, cre],
  Chen Xu [aut],
  Kelly Burkett [aut]
Authors@R: c(person(given = "Qianxiang",
                        family = "Zang",
                        role = c("aut","cre"),
                        email = "SMLEmaintainer@gmail.com"),
                 person(given = "Chen",
                        family = "Xu",
                        role = "aut"),
                 person(given = "Kelly",
                        family = "Burkett",
                        role = "aut")
			    )
Maintainer: Qianxiang Zang <SMLEmaintainer@gmail.com>
Repository: CRAN
Packaged: 2026-01-18 14:02:37 UTC; 15802
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
Date/Publication: 2026-01-18 23:40:19 UTC
Built: R 4.6.0; ; 2026-03-10 03:39:59 UTC; windows
