{ "_id": "6a28685b732311cd87586ecc", "Package": "CKNNRLD", "Title": "Clustering-Based K-Nearest Neighbor Regression for Longitudinal\nData", "Version": "0.1.4", "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", "NeedsCompilation": "no", "Language": "en-US", "Config/roxygen2/version": "8.0.0", "Packaged": { "Date": "2026-06-09 19:19:52 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 ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-06-09 16:20:02 UTC", "RemoteUrl": "https://github.com/cran/CKNNRLD", "RemoteRef": "HEAD", "RemoteSha": "0963fe9096fc71bfefaff713d23890c1dd80d332", "MD5sum": "b9f408be5718c3f40c2c3635620ff004", "_user": "cran", "_type": "src", "_file": "CKNNRLD_0.1.4.tar.gz", "_fileid": 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