{ "_id": "6a1f14edb401979e7341e3f7", "Package": "fusedTree", "Title": "Fused Partitioned Regression for Clinical and Omics Data", "Version": "1.1.0", "Authors@R": "c(person(c(\"Jeroen\", \"M.\"), \"Goedhart\", , \"jeroengoed@gmail.com\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0003-0134-1897\")),\nperson(c(\"Wessel\", \"N.\"), \"van Wieringen\", role = \"aut\", comment = \"Author of 'porridge' 'R' package, from which many functionalities have been adopted\"),\nperson(\"Thomas\", \"Klausch\", role = \"ths\"),\nperson(c(\"Mark\",\"A.\"), \"van de Wiel\", role = \"ths\"),\nperson(\"Hanarth Fonds\", role = \"fnd\"))", "Description": "Fit (generalized) linear regression models in each leaf\nnode of a tree. The tree is constructed using clinical\nvariables only. The linear regression models are constructed\nusing (high-dimensional) omics variables only. The\nleaf-node-specific regression models are estimated using the\npenalized likelihood including a standard ridge (L2) penalty\nand a fusion penalty that links the leaf-node-specific\nregression models to one another. The intercepts of the leaf\nnodes reflect the effects of the clinical variables and are\nleft unpenalized. The tree, fitted with the clinical variables\nonly, should be constructed outside of the package with the\n'rpart' 'R' package. See Goedhart and others (2024)\n for details on the method.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "Repository": "https://jeroengoedhart.r-universe.dev", "Date/Publication": "2025-08-20 07:57:23 UTC", "RemoteUrl": "https://github.com/jeroengoedhart/fusedtree", "RemoteRef": "HEAD", "RemoteSha": "6490422905c2e33639a5cc6b6f10b3db96a1d7df", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-17 06:51:03 UTC", "User": "root" }, "Author": "Jeroen M. 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