{ "_id": "6a140215acfb0bcc41d3863c", "Package": "VFP", "Version": "1.4.4", "Date": "2025-04-08", "Title": "Variance Function Program", "Author": "Andre Schuetzenmeister [cre, aut], Florian Dufey [aut], Andrea\nGeistanger [ctb]", "Maintainer": "Andre Schuetzenmeister ", "Authors@R": "c(\nperson(given=\"Andre\", family=\"Schuetzenmeister\", email=\"andre.schuetzenmeister@roche.com\", role = c(\"cre\", \"aut\")),\nperson(given=\"Florian\", family=\"Dufey\", email=\"florian.dufey@roche.com\", role = c(\"aut\")),\nperson(given=\"Andrea\", family=\"Geistanger\", email=\"andrea.geistanger@roche.com\", role = c(\"ctb\"))\n)", "Description": "Variance function estimation for models proposed by W.\nSadler in his variance function program ('VFP',\nwww.aacb.asn.au/AACB/Resources/Variance-Function-Program).\nHere, the idea is to fit multiple variance functions to a data\nset and consequently assess which function reflects the\nrelationship 'Var ~ Mean' best. For 'in-vitro diagnostic'\n('IVD') assays modeling this relationship is of great\nimportance when individual test-results are used for defining\nfollow-up treatment of patients.", "License": "GPL (>= 2)", "VignetteBuilder": "knitr, rmarkdown", "RoxygenNote": "7.2.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-25 07:59:11 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2025-04-08 12:10:02 UTC", "RemoteUrl": "https://github.com/cran/VFP", "RemoteRef": "HEAD", "RemoteSha": "fc6b2e34c6bf6e42e2244786c3d31335d0676f19", "MD5sum": "fc511d3ee2d98442ea6970d5a1db3ce3", "_user": "cran", "_type": "src", "_file": "VFP_1.4.4.tar.gz", "_fileid": "9cd592cb8d867c46aac500c0f197b77e7c82b0cc4dcc5002cd37268479fd8f9a", "_filesize": 2949525, "_sha256": "9cd592cb8d867c46aac500c0f197b77e7c82b0cc4dcc5002cd37268479fd8f9a", "_created": "2026-05-25T07:59:11.000Z", "_published": "2026-05-25T08:02:29.649Z", "_distro": "noble", "_jobs": [ { "job": 77677443950, 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