Package: sparsenetgls
Type: Package
Title: Using Gaussian graphical structue learning estimation in
        generalized least squared regression for multivariate normal
        regression
Version: 1.28.0
Authors@R: c(person("Irene", "Zeng", role = c("aut", "cre"),
            email = "szen003@aucklanduni.ac.nz"),
            person("Thomas", "Lumley", role = "ctb", email = "t.lumey@auckland.ac.nz"))
Description: The package provides methods of combining the graph
        structure learning and generalized least squares regression to
        improve the regression estimation. The main function
        sparsenetgls() provides solutions for multivariate regression
        with Gaussian distributed dependant variables and explanatory
        variables utlizing multiple well-known graph structure learning
        approaches to estimating the precision matrix, and uses a
        penalized variance covariance matrix with a distance tuning
        parameter of the graph structure in deriving the sandwich
        estimators in generalized least squares (gls) regression. This
        package also provides functions for assessing a Gaussian
        graphical model which uses the penalized approach. It uses
        Receiver Operative Characteristics curve as a visualization
        tool in the assessment.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0), Matrix, MASS
Imports: methods, glmnet, huge, stats, graphics, utils
Suggests: testthat, lme4, BiocStyle, knitr, rmarkdown, roxygen2 (>=
        5.0.0)
NeedsCompilation: no
URL:
RoxygenNote: 6.0.1
biocViews: ImmunoOncology,
        GraphAndNetwork,Regression,Metabolomics,CopyNumberVariation,MassSpectrometry,Proteomics,Software,Visualization
bugReport: https://github.com/superOmics/sparsenetgls/issues
VignetteBuilder: knitr
SystemRequirements: GNU make
Config/pak/sysreqs: libglpk-dev make libxml2-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 14:47:32 UTC
RemoteUrl: https://github.com/bioc/sparsenetgls
RemoteRef: RELEASE_3_22
RemoteSha: ea9f5070a07aa0bc6be53dfb7001dccbf68c75e4
Packaged: 2025-11-11 17:41:28 UTC; root
Author: Irene Zeng [aut, cre],
  Thomas Lumley [ctb]
Maintainer: Irene Zeng <szen003@aucklanduni.ac.nz>
Built: R 4.5.2; ; 2025-11-11 17:42:55 UTC; windows
