{ "_id": "6a54d378ff0138dec5d67117", "Package": "CKNNRLD", "Title": "Clustering-Based K-Nearest Neighbor Regression for Longitudinal\nData", "Version": "0.2.2", "Authors@R": "c(\nperson(given = \"Mohammad Sadegh\", family = \"Loeloe\", email = \"mslbiostat@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(given = \"Seyyed Mohammad\", family = \"Tabatabaei\", role = \"aut\"),\nperson(given = \"Reyhane\", family = \"Sefidkar\", role = \"aut\"),\nperson(given = \"Amir Houshang\", family = \"Mehrparvar\", role = \"aut\"),\nperson(given = \"Sara\", family = \"Jambarsang\", role = c(\"aut\", \"ths\"))\n)", "Description": "Implements the 'CKNNRLD' algorithm (Clustering-Based\nK-Nearest Neighbor Regression for Longitudinal Data) for\nimproving K-Nearest Neighbor ('KNN') regression on longitudinal\ndata through cluster-based partitioning and localized\nprediction. Offers enhanced computational efficiency and\naccuracy for high-volume longitudinal datasets. The acronym\n'KNN' stands for K-Nearest Neighbor. References: Loeloe MS,\nTabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025).\n\"Boosting K-nearest neighbor regression performance for\nlongitudinal data through a novel learning approach.\" BMC\nBioinformatics, 26, 232. .", "License": "GPL-3", "Encoding": "UTF-8", "RoxygenNote": "8.0.0", "NeedsCompilation": "no", "Language": "en-US", "LazyData": "true", "Packaged": { "Date": "2026-07-13 11:54:49 UTC", "User": "root" }, "Author": "Mohammad Sadegh Loeloe [aut, cre], Seyyed Mohammad Tabatabaei\n[aut], Reyhane Sefidkar [aut], Amir Houshang Mehrparvar [aut],\nSara Jambarsang [aut, ths]", "Maintainer": "Mohammad Sadegh Loeloe ", "Config/pak/sysreqs": "libabsl-dev cmake libfreetype6-dev libgdal-dev\ngdal-bin libgeos-dev libglu1-mesa-dev make texlive libpng-dev\nlibuv1-dev libgl1-mesa-dev libssl-dev libproj-dev\nlibsqlite3-dev libudunits2-dev zlib1g-dev", "Repository": "https://mslbiostat.r-universe.dev", "Date/Publication": "2026-07-13 07:20:08 UTC", "RemoteUrl": 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