{ "_id": "6a2510e54b233be198389d4c", "Package": "yager", "Title": "Yet Another General Regression Neural Network", "Version": "0.1.1", "Author": "WenSui Liu", "Maintainer": "WenSui Liu ", "Description": "Another implementation of general regression neural\nnetwork in R based on Specht (1991) . It\nis applicable to the functional approximation or the\nclassification.", "URL": "https://github.com/statcompute/yager", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-07 06:31:28 UTC", "User": "root" }, "Repository": "https://statcompute.r-universe.dev", "Date/Publication": "2020-10-25 17:30:02 UTC", "RemoteUrl": "https://github.com/cran/yager", "RemoteRef": "HEAD", "RemoteSha": "d9dbdd097273d4da0104192f8cc4473073fe8500", "MD5sum": "2679262bd84dca7a2a09befd1062ed0b", "_user": "statcompute", "_type": "src", "_file": "yager_0.1.1.tar.gz", "_fileid": "f5fb3d89e94415713dd1f1a88238d24e15fec5951250a2ae27a410128cec7e7b", "_filesize": 111087, "_sha256": "f5fb3d89e94415713dd1f1a88238d24e15fec5951250a2ae27a410128cec7e7b", "_created": "2026-06-07T06:31:28.000Z", "_published": "2026-06-07T06:34:13.931Z", "_distro": "noble", "_jobs": [ { "job": 79937633714, "time": 105, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7461486166" }, { "job": 79937633700, "time": 105, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7461486310" }, { "job": 79937633687, "time": 81, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7461483100" }, { "job": 79937633696, "time": 111, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7461486927" }, { "job": 79937476999, "time": 152, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7461472951" }, { "job": 79937633681, "time": 92, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7461484485" }, { "job": 79937633716, "time": 75, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7461482540" }, { "job": 79937633715, "time": 130, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7461489749" }, { "job": 79937633717, "time": 67, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7461481362" } ], "_buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/yager", "_commit": { "id": "d9dbdd097273d4da0104192f8cc4473073fe8500", "author": "WenSui Liu ", "committer": "cran-robot ", "message": "version 0.1.1\n", "time": 1603647002 }, "_maintainer": { "name": "WenSui Liu", "email": "liuwensui@gmail.com", "login": "statcompute", "description": "", "uuid": 4590938 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.6.0", "role": "Depends" }, { "package": "datasets", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "randtoolbox", "role": "Imports" }, { "package": "lhs", "role": "Imports" }, { "package": "MLmetrics", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "parallel", "role": "Imports" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "statcompute", "count": 2, "uuid": 4590938 } ], "_userbio": { "uuid": 4590938, "type": "user", "name": "WenSui Liu" }, "_downloads": { "count": 152, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/yager" }, "_devurl": "https://github.com/statcompute/yager", "_searchresults": 2, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/yager.html", "manual.pdf" ], "_realowner": "statcompute", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2020-01-14" }, { "version": "0.1.1", "date": "2020-10-25" } ], "_exports": [ "folds", "gen_latin", "gen_sobol", "gen_unifm", "grnn.fit", "grnn.imp", "grnn.margin", "grnn.optmiz_auc", "grnn.parpred", "grnn.partial", "grnn.pfi", "grnn.predict", "grnn.predone", "grnn.search_auc", "grnn.search_rsq", "grnn.x_imp", "grnn.x_pfi" ], "_help": [ { "page": "folds", "title": "Generate a list of index for the n-fold cross-validation", "topics": [ "folds" ] }, { "page": "gen_latin", "title": "Generate random numbers of latin hypercube sampling", "topics": [ "gen_latin" ] }, { "page": "gen_sobol", "title": "Generate sobol sequence", "topics": [ "gen_sobol" ] }, { "page": "gen_unifm", "title": "Generate Uniform random numbers", "topics": [ "gen_unifm" ] }, { "page": "grnn.fit", "title": "Create a general regression neural network", "topics": [ "grnn.fit" ] }, { "page": "grnn.imp", "title": "Derive the importance rank of all predictors used in the GRNN", "topics": [ "grnn.imp" ] }, { "page": "grnn.margin", "title": "Derive the marginal effect of a predictor used in a GRNN", "topics": [ "grnn.margin" ] }, { "page": "grnn.optmiz_auc", "title": "Optimize the optimal value of GRNN smoothing parameter based on AUC", "topics": [ "grnn.optmiz_auc" ] }, { "page": "grnn.parpred", "title": "Calculate predicted values of GRNN by using parallelism", "topics": [ "grnn.parpred" ] }, { "page": "grnn.partial", "title": "Derive the partial effect of a predictor used in a GRNN", "topics": [ "grnn.partial" ] }, { "page": "grnn.pfi", "title": "Derive the PFI rank of all predictors used in the GRNN", "topics": [ "grnn.pfi" ] }, { "page": "grnn.predict", "title": "Calculate predicted values of GRNN", "topics": [ "grnn.predict" ] }, { "page": "grnn.predone", "title": "Calculate a predicted value of GRNN", "topics": [ "grnn.predone" ] }, { "page": "grnn.search_auc", "title": "Search for the optimal value of GRNN smoothing parameter based on AUC", "topics": [ "grnn.search_auc" ] }, { "page": "grnn.search_rsq", "title": "Search for the optimal value of GRNN smoothing parameter based on r-square", "topics": [ "grnn.search_rsq" ] }, { "page": "grnn.x_imp", "title": "Derive the importance of a predictor used in the GRNN", "topics": [ "grnn.x_imp" ] }, { "page": "grnn.x_pfi", "title": "Derive the permutation feature importance of a predictor used in the GRNN", "topics": [ "grnn.x_pfi" ] } ], "_rundeps": [ "bitops", "caTools", "gplots", "gtools", "KernSmooth", "lhs", "MLmetrics", "randtoolbox", "Rcpp", "rngWELL", "ROCR" ], "_score": 1, "_indexed": true, "_nocasepkg": "yager", "_universes": [ "statcompute" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.1", "date": "2026-06-07T06:33:16.000Z", "distro": "noble", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "6993c30d2581fde81d122e77656f5b0d93a9dfd766f1b8865c46e9569dc00aa3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.6.0", "os": "linux", "version": "0.1.1", "date": "2026-06-07T06:33:16.000Z", "distro": "noble", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "6313bb3677b6d1458c2d828954bbdfdce835265c947ea555426c36e6b8370082", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.5.3", "os": "mac", "version": "0.1.1", "date": "2026-06-07T06:32:55.000Z", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "6d6a1a1949410de163b27c59cb3265557507cf5e154f4f6fb5eb9634f8e279fc", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.6.0", "os": "mac", "version": "0.1.1", "date": "2026-06-07T06:33:21.000Z", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "ce6fcb149fc8edb29f6dc3287caec7d69311781b20fd672b5ec21661c8868b15", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.1", "date": "2026-06-07T06:33:17.000Z", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "6653b8d6d424b833feba378bb9a174e812cdab30d48f9339ad10c1daf9e50fa1", "status": "success", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.7.0", "os": "win", "version": "0.1.1", "date": "2026-06-07T06:32:41.000Z", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "31b30ece1fa56c64a727bd5c1b94ee246386f2a699414f6e3c05812fd42bdec8", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.5.3", "os": "win", "version": "0.1.1", "date": "2026-06-07T06:33:36.000Z", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "8fc6ae3774f4f1fedab9944b3dea8ddfdb0f5cd8128b880970a77444c3a27451", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" }, { "r": "4.6.0", "os": "win", "version": "0.1.1", "date": "2026-06-07T06:32:32.000Z", "commit": "d9dbdd097273d4da0104192f8cc4473073fe8500", "fileid": "0e333a68491e59850e3828e8a1f8628d8e800913500541edb1e5f49cacbc0285", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/statcompute/actions/runs/27084948286" } ] }