Package: gif
Type: Package
Version: 0.1.1
Title: Graphical Independence Filtering
Description: Provides a method of recovering the precision matrix for
        Gaussian graphical models efficiently. Our approach could be
        divided into three categories. First of all, we use Hard
        Graphical Thresholding for best subset selection problem of
        Gaussian graphical model, and the core concept of this method
        was proposed by Luo et al. (2014) <arXiv:1407.7819>. Secondly,
        a closed form solution for graphical lasso under acyclic graph
        structure is implemented in our package (Fattahi and Sojoudi
        (2019) <https://jmlr.org/papers/v20/17-501.html>). Furthermore,
        we implement block coordinate descent algorithm to efficiently
        solve the covariance selection problem (Dempster (1972)
        <doi:10.2307/2528966>). Our package is computationally
        efficient and can solve ultra-high-dimensional problems, e.g. p
        > 10,000, in a few minutes.
Authors@R: c(
    person("Shiyun", "Lin", , "linshy27@mail2.sysu.edu.cn", role = c("aut", "cre")),
    person("Jin", "Zhu", , role = "aut"),
    person("Junxian", "Zhu", , role = "aut"),
    person("Xueqin", "Wang", , role = "aut"),
    person("SC2S2", role = c("cph"))
    )
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2)
Imports: Rcpp (>= 0.12.15), MASS, Matrix
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Author: Shiyun Lin [aut, cre], Jin Zhu [aut], Junxian Zhu [aut], Xueqin
        Wang [aut], SC2S2 [cph]
Maintainer: Shiyun Lin <linshy27@mail2.sysu.edu.cn>
RoxygenNote: 7.1.0
Packaged: 2026-06-17 09:11:29 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2024-01-13 02:39:01 UTC
RemoteUrl: https://github.com/cran/gif
RemoteRef: HEAD
RemoteSha: d579dcd833bd9d42a872ffac0f7285bac0ba4f7a