{ "_id": "6a103e4eacfb0bcc41c9c8a0", "Package": "VIM", "Version": "7.1.0", "Title": "Visualization and Imputation of Missing Values", "Authors@R": "c(\nperson(\"Matthias\", \"Templ\", email = \"matthias.templ@gmail.com\", role = c(\"aut\",\"cre\")),\nperson(\"Alexander\", \"Kowarik\", email = \"alexander.kowarik@statistik.gv.at\", role = c(\"aut\"), comment=c(ORCID=\"0000-0001-8598-4130\")),\nperson(\"Andreas\", \"Alfons\", role = c(\"aut\")),\nperson(\"Johannes\", \"Gussenbauer\", role = c(\"aut\")),\nperson(\"Nina\", \"Niederhametner\", role = c(\"aut\")),\nperson(\"Eileen\", \"Vattheuer\", role = c(\"aut\")),\nperson(\"Gregor\", \"de Cillia\", email = \"gregor.decillia@statistik.gv.at\", role = c(\"aut\")),\nperson(\"Bernd\", \"Prantner\", role = c(\"ctb\")),\nperson(\"Wolfgang\", \"Rannetbauer\", role = c(\"aut\"))\n)", "Description": "Provides methods for imputation and visualization of\nmissing values. It includes graphical tools to explore the\namount, structure and patterns of missing and/or imputed\nvalues, supporting exploratory data analysis and helping to\ninvestigate potential missingness mechanisms (details in\nAlfons, Templ and Filzmoser, .\nThe quality of imputations can be assessed visually using a\nwide range of univariate, bivariate and multivariate plots. The\npackage further provides several imputation methods, including\nefficient implementations of k-nearest neighbour and hot-deck\nimputation (Kowarik and Templ 2013,\n, iterative robust model-based\nmultiple imputation (Templ 2011,\n; Templ 2023,\n), and machine learning–based\napproaches such as robust GAM-based multiple imputation (Templ\n2024, ) as well as gradient\nboosting (XGBoost) and transformer-based methods\n(Niederhametner et al., ).\nGeneral background and practical guidance on imputation are\nprovided in the Springer book by Templ (2023)\n.", "LazyData": "TRUE", "ByteCompile": "TRUE", "License": "GPL (>= 2)", "URL": "https://github.com/statistikat/VIM", "RoxygenNote": "7.3.3", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "Config/pak/sysreqs": "cmake make libicu-dev", "Repository": "https://statistikat.r-universe.dev", "Date/Publication": "2026-03-12 09:47:38 UTC", "RemoteUrl": "https://github.com/statistikat/vim", "RemoteRef": 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