{ "_id": "6a5f37ab14e95619b75d5acf", "Package": "BrainCon", "Type": "Package", "Title": "Inference the Partial Correlations Based on Time Series Data", "Version": "0.3.0", "Author": "Yunhaonan Yang [aut, cre], Peng Wu [aut], Xin Gai [aut], Yumou\nQiu [aut], Xiaohua Zhou [aut]", "Authors@R": "c(\nperson(\"Yunhaonan\", \"Yang\", email = \"haonan_yy@pku.edu.cn\", role = c(\"aut\", \"cre\")),\nperson(\"Peng\", \"Wu\", email = \"wupeng@bicmr.pku.edu.cn\", role = \"aut\"),\nperson(\"Xin\", \"Gai\", email = \"gaitianmu@outlook.com\", role = \"aut\"),\nperson(\"Yumou\", \"Qiu\", email = \"yumouqiu@iastate.edu\", role = \"aut\"),\nperson(\"Xiaohua\", \"Zhou\", email = \"azhou@math.pku.edu.cn\", role = \"aut\"))", "Maintainer": "Yunhaonan Yang ", "Description": "A statistical tool to inference the multi-level partial\ncorrelations based on multi-subject time series data,\nespecially for brain functional connectivity. It combines both\nindividual and population level inference by using the methods\nof Qiu and Zhou. (2021) and\nGenovese and Wasserman. (2006). It realizes two reliable\nestimation methods of partial correlation coefficients, using\nscaled lasso and lasso. It can be used to estimate individual-\nor population-level partial correlations, identify nonzero\nones, and find out unequal partial correlation coefficients\nbetween two populations.", "License": "GPL (>= 2)", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-21 09:06:31 UTC", "User": "root" }, "Repository": "https://cemrclinicencoding.r-universe.dev", "Date/Publication": "2023-05-22 05:50:02 UTC", "RemoteUrl": "https://github.com/cran/BrainCon", "RemoteRef": "HEAD", "RemoteSha": "4e5832a19b3802c1b61770929807aaa1e365596b", "_user": "cemrclinicencoding", "_type": "src", "_file": "BrainCon_0.3.0.tar.gz", "_fileid": "https://r2.ropensci.org/c3e1198aacaab3e490a1dfcd6b8571fa3de005b7af515fad69337882766a67ca", "_filesize": 306185, "_sha256": "c3e1198aacaab3e490a1dfcd6b8571fa3de005b7af515fad69337882766a67ca", "_expires": "2026-10-29T09:11:05.000Z", "_created": "2026-07-21T09:06:31.000Z", "_published": "2026-07-21T09:11:07.361Z", "_jobs": [ { "job": 88590408795, "time": 139, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "8489785652" }, { "job": 88590408566, "time": 144, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "8489787916" }, { "job": 88590408497, "time": 231, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "8489808483" }, { "job": 88590408535, "time": 190, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "8489791368" }, { "job": 88589944513, "time": 126, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "8489721962" }, { "job": 88590408476, "time": 97, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "8489766287" }, { "job": 88590408557, "time": 94, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "8489764578" }, { "job": 88590408574, "time": 98, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "8489766582" }, { "job": 88590408494, "time": 89, "config": "windows-release", "r": "4.6.1", "check": "OK", "artifact": "8489762645" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905", "_status": "success", "_upstream": "https://github.com/cran/BrainCon", "_commit": { "id": "4e5832a19b3802c1b61770929807aaa1e365596b", "author": "Yunhaonan Yang ", "committer": "cran-robot ", "message": "version 0.3.0\n", "time": 1684734602 }, "_maintainer": { "name": "Yunhaonan Yang", "email": "haonan_yy@pku.edu.cn", "login": "cemrclinicencoding", "description": "", "uuid": 91713792 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 2.10", "role": "Depends" }, { "package": "glmnet", "role": "Imports" }, { "package": "MASS", "role": "Imports" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "cemrclinicencoding", "count": 3, "uuid": 91713792 } ], "_userbio": { "uuid": 91713792, "type": "user", "name": "CEMRclinicencoding", "followers": 0 }, "_downloads": { "count": 270, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/BrainCon" }, "_searchresults": 0, "_rbuild": "4.6.1", "_assets": [ "extra/BrainCon.html", "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "manual.pdf" ], "_realowner": "cemrclinicencoding", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2021-09-30" }, { "version": "0.2.0", "date": "2022-04-21" }, { "version": "0.3.0", "date": "2023-05-22" } ], "_exports": [ "individual.est", "individual.test", "normalize.set", "population.est", "population.test", "population.test.MinPv", "population2sample.test", "population2sample.test.MinPv", "QS", "scaledlasso" ], "_datasets": [ { "name": "indsim", "title": "Simulation time series data for individual", "object": "indsim", "class": [ "matrix", "array" ], "fields": [], "rows": 50, "table": true, "tojson": true }, { "name": "popsimA", "title": "Simulation time series data for population A", "object": "popsimA", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "popsimB", "title": "Simulation time series data for population B", "object": "popsimB", "class": [ "array" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "individual.est", "title": "Estimate individual-level partial correlation coefficients", "topics": [ "individual.est" ] }, { "page": "individual.test", "title": "Identify nonzero individual-level partial correlations", "topics": [ "individual.test" ] }, { "page": "indsim", "title": "Simulation time series data for individual", "topics": [ "indsim" ] }, { "page": "popsimA", "title": "Simulation time series data for population A", "topics": [ "popsimA" ] }, { "page": "popsimB", "title": "Simulation time series data for population B", "topics": [ "popsimB" ] }, { "page": "population.est", "title": "Estimate population-level partial correlation coefficients", "topics": [ "population.est" ] }, { "page": "population.test", "title": "The one-sample population inference", "topics": [ "population.test" ] }, { "page": "population.test.MinPv", "title": "The one-sample population inference using Genovese and Wasserman's method", "topics": [ "population.test.MinPv" ] }, { "page": "population2sample.test", "title": "Identify differences of partial correlations between two populations", "topics": [ "population2sample.test" ] }, { "page": "population2sample.test.MinPv", "title": "Identify differences of partial correlations between two populations using Genovese and Wasserman's method", "topics": [ "population2sample.test.MinPv" ] } ], "_rundeps": [ "codetools", "foreach", "glmnet", "iterators", "lattice", "MASS", "Matrix", "Rcpp", "RcppEigen", "shape", "survival" ], "_score": 1, "_indexed": true, "_nocasepkg": "braincon", "_universes": [ "cemrclinicencoding" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.3.0", "date": "2026-07-21T09:08:31.000Z", "distro": "resolute", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/7f98745a62aeb146c351e5e1ac6af0ae885fe92f5f5db69ab0b43725fbfabe3e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.6.1", "os": "linux", "version": "0.3.0", "date": "2026-07-21T09:08:44.000Z", "distro": "resolute", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/a50955ef1d7d3a1f5dccee8985315415f72d8ddc6dd3e98382f452149881411a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.5.3", "os": "mac", "version": "0.3.0", "date": "2026-07-21T09:09:21.000Z", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/c41e5bd0949043c954bebe2fcd370dc6b27b904dde3929dbc8618fbbe2326a7e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.6.1", "os": "mac", "version": "0.3.0", "date": "2026-07-21T09:08:50.000Z", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/671cf78ec5c1742744281d25ead015d199321116dae37e7458df281960f0ce4c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.6.0", "os": "wasm", "version": "0.3.0", "date": "2026-07-21T09:08:26.000Z", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/60a86a74b7072f480a5e6c10a0c9539bb978482e6996caaa54b573ca4453b090", "status": "success", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.7.0", "os": "win", "version": "0.3.0", "date": "2026-07-21T09:07:34.000Z", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/52b3204fb9cf3d0599d22a81843a0001e6511c8bbc8cba4621c001ba19b7d510", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.5.3", "os": "win", "version": "0.3.0", "date": "2026-07-21T09:07:46.000Z", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/0938a57d2248b54456a49aac2b445d3809d2ce52bd43e8f5265849c6749437eb", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" }, { "r": "4.6.1", "os": "win", "version": "0.3.0", "date": "2026-07-21T09:07:34.000Z", "commit": "4e5832a19b3802c1b61770929807aaa1e365596b", "fileid": "https://r2.ropensci.org/b26838017ed0044103dc11a69841817a36516606bba5996a4f3b942fbd4d7e5b", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cemrclinicencoding/actions/runs/29816767905" } ] }