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Functions are designed to\nbe transparent and report optimization diagnostics where\napplicable. For Gaussian graphical models, the graphical lasso\nstationarity (Karush-Kuhn-Tucker) residual quantifies the\ndeviation of the estimated solution from the optimum of the\ncorresponding convex optimization problem.", "License": "GPL-3", "URL": "https://pak.dynasite.org/psychnets,\nhttps://github.com/mohsaqr/psychnets", "BugReports": "https://github.com/mohsaqr/psychnets/issues", "Encoding": "UTF-8", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Repository": "https://mohsaqr.r-universe.dev", "Date/Publication": "2026-10-16 15:00:40 UTC", "RemoteUrl": "https://github.com/mohsaqr/psychnets", "RemoteRef": "HEAD", "RemoteSha": "aa81f15043b66401ab498238490c3d4480914eb5", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-16 17:40:42 UTC", "User": "root" }, "Author": "Mohammed Saqr [aut, cre, cph],\nSonsoles López-Pernas [aut]", "Maintainer": "Mohammed Saqr ", "_user": "mohsaqr", "_type": 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