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The main function\nsparsenetgls() provides solutions for multivariate regression\nwith Gaussian distributed dependant variables and explanatory\nvariables utlizing multiple well-known graph structure learning\napproaches to estimating the precision matrix, and uses a\npenalized variance covariance matrix with a distance tuning\nparameter of the graph structure in deriving the sandwich\nestimators in generalized least squares (gls) regression. This\npackage also provides functions for assessing a Gaussian\ngraphical model which uses the penalized approach. It uses\nReceiver Operative Characteristics curve as a visualization\ntool in the assessment.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "NeedsCompilation": "no", "URL": "", "RoxygenNote": "6.0.1", "biocViews": "ImmunoOncology,\nGraphAndNetwork,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.r-universe.dev", "Date/Publication": "2026-04-28 12:48:41 UTC", "RemoteUrl": "https://github.com/bioc/sparsenetgls", "RemoteRef": "HEAD", "RemoteSha": "4baecb048db05ce38811b569adf497e3be59a81c", "Packaged": { "Date": "2026-05-30 09:49:24 UTC", "User": "root" }, "Author": "Irene Zeng [aut, cre],\nThomas Lumley [ctb]", "Maintainer": "Irene Zeng ", "MD5sum": "26e0929f8d019fa23a0e822714a5247e", "_user": "bioc", "_type": "src", 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