{
  "_id": "6a1ebb54b25058d4daae1160",
  "Package": "bpnreg",
  "Type": "Package",
  "Title": "Bayesian Projected Normal Regression Models for Circular Data",
  "Version": "2.0.3",
  "Authors@R": "person(\"Jolien\", \"Cremers\", email = \"joliencremers@gmail.com\",\nrole = c(\"aut\", \"cre\"))",
  "Description": "Fitting Bayesian multiple and mixed-effect regression\nmodels for circular data based on the projected normal\ndistribution. Both continuous and categorical predictors can be\nincluded. Sampling from the posterior is performed via an MCMC\nalgorithm. Posterior descriptives of all parameters, model fit\nstatistics and Bayes factors for hypothesis tests for\ninequality constrained hypotheses are provided. See Cremers,\nMulder & Klugkist (2018) <doi:10.1111/bmsp.12108> and\nNuñez-Antonio & Guttiérez-Peña (2014)\n<doi:10.1016/j.csda.2012.07.025>.",
  "License": "GPL-3",
  "URL": "https://github.com/joliencremers/bpnreg",
  "BugReports": "https://github.com/joliencremers/bpnreg/issues",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.2.3",
  "VignetteBuilder": "knitr",
  "Config/pak/sysreqs": "make libx11-dev zlib1g-dev",
  "Repository": "https://joliencremers.r-universe.dev",
  "Date/Publication": "2023-11-02 12:15:53 UTC",
  "RemoteUrl": "https://github.com/joliencremers/bpnreg",
  "RemoteRef": "HEAD",
  "RemoteSha": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-02 11:09:56 UTC",
    "User": "root"
  },
  "Author": "Jolien Cremers [aut, cre]",
  "Maintainer": "Jolien Cremers <joliencremers@gmail.com>",
  "MD5sum": "827b90607ef4da643b26c0b9a127935c",
  "_user": "joliencremers",
  "_type": "src",
  "_file": "bpnreg_2.0.3.tar.gz",
  "_fileid": "f1d74bcf559dad3c8c175fd959a3ff47c229a67ecf80e000bebfa99eb2c8c81c",
  "_filesize": 247771,
  "_sha256": "f1d74bcf559dad3c8c175fd959a3ff47c229a67ecf80e000bebfa99eb2c8c81c",
  "_created": "2026-06-02T11:09:56.000Z",
  "_published": "2026-06-02T11:15:32.109Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 79057499877,
      "time": 181,
      "config": "linux-devel-arm64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7356120118"
    },
    {
      "job": 79057499973,
      "time": 189,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7356121791"
    },
    {
      "job": 79057499834,
      "time": 172,
      "config": "linux-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356117064"
    },
    {
      "job": 79057499897,
      "time": 174,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356116925"
    },
    {
      "job": 79057499891,
      "time": 177,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7356145211"
    },
    {
      "job": 79057499767,
      "time": 250,
      "config": "macos-oldrel-x86_64",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7356144162"
    },
    {
      "job": 79057499790,
      "time": 137,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356106363"
    },
    {
      "job": 79057499871,
      "time": 220,
      "config": "macos-release-x86_64",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356141618"
    },
    {
      "job": 79056745226,
      "time": 280,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356056357"
    },
    {
      "job": 79057499776,
      "time": 139,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356105817"
    },
    {
      "job": 79057499764,
      "time": 193,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "OK",
      "artifact": "7356122957"
    },
    {
      "job": 79057499770,
      "time": 161,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "OK",
      "artifact": "7356112379"
    },
    {
      "job": 79057499818,
      "time": 147,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7356108422"
    }
  ],
  "_buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/joliencremers/bpnreg",
  "_commit": {
    "id": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
    "author": "joliencremers <joliencremers@gmail.com>",
    "committer": "joliencremers <joliencremers@gmail.com>",
    "message": "development version 2.0.3.9000\n",
    "time": 1698927353
  },
  "_maintainer": {
    "name": "Jolien Cremers",
    "email": "joliencremers@gmail.com",
    "login": "joliencremers",
    "description": "",
    "uuid": 10900828
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 3.6.0",
      "role": "Depends"
    },
    {
      "package": "Rcpp",
      "version": ">= 1.0.2",
      "role": "LinkingTo"
    },
    {
      "package": "RcppArmadillo",
      "version": ">= 0.10.1.2.0",
      "role": "LinkingTo"
    },
    {
      "package": "BH",
      "version": ">= 1.69.0.1",
      "role": "LinkingTo"
    },
    {
      "package": "Rcpp",
      "version": ">= 1.0.2",
      "role": "Imports"
    },
    {
      "package": "haven",
      "version": ">= 2.1.1",
      "role": "Imports"
    },
    {
      "package": "methods",
      "version": ">= 3.6.0",
      "role": "Imports"
    },
    {
      "package": "qpdf",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    }
  ],
  "_owner": "joliencremers",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 15,
  "_contributors": [
    {
      "user": "joliencremers",
      "count": 261,
      "uuid": 10900828
    },
    {
      "user": "arjanhuizing",
      "count": 1,
      "uuid": 33631683
    },
    {
      "user": "keesmulder",
      "count": 1,
      "uuid": 7806295
    }
  ],
  "_userbio": {
    "uuid": 10900828,
    "type": "user",
    "name": "joliencremers"
  },
  "_downloads": {
    "count": 305,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/bpnreg"
  },
  "_mentions": 1,
  "_devurl": "https://github.com/joliencremers/bpnreg",
  "_searchresults": 100,
  "_topics": [
    "openblas",
    "cpp",
    "openmp"
  ],
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/bpnreg.html",
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/joliencremers/bpnreg",
  "_realowner": "joliencremers",
  "_cranurl": true,
  "_releases": [
    {
      "version": "1.0.0",
      "date": "2018-02-27"
    },
    {
      "version": "1.0.1",
      "date": "2019-11-05"
    },
    {
      "version": "1.0.2",
      "date": "2019-12-08"
    },
    {
      "version": "1.0.3",
      "date": "2020-02-04"
    },
    {
      "version": "2.0.0",
      "date": "2021-03-02"
    },
    {
      "version": "2.0.1",
      "date": "2021-03-23"
    },
    {
      "version": "2.0.2",
      "date": "2021-08-06"
    },
    {
      "version": "2.0.3",
      "date": "2024-01-15"
    }
  ],
  "_exports": [
    "BFc",
    "bpnme",
    "bpnr",
    "coef_circ",
    "coef_lin",
    "coef_ran",
    "fit",
    "hpd_est",
    "hpd_est_circ",
    "mean_circ",
    "mode_est",
    "mode_est_circ",
    "rho_circ",
    "sd_circ",
    "traceplot"
  ],
  "_datasets": [
    {
      "name": "Maps",
      "title": "The geometry of human knowledge of navigation space.",
      "object": "Maps",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Subject",
        "Maze",
        "Trial.no",
        "Trial.type",
        "Error",
        "Learn",
        "Error.rad",
        "L.c"
      ],
      "rows": 160,
      "table": true,
      "tojson": true
    },
    {
      "name": "Motor",
      "title": "Phase differences in hand flexion-extension movements.",
      "object": "Motor",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Cond",
        "PhaseDiff",
        "AvAmp",
        "Phaserad"
      ],
      "rows": 42,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "BFc",
      "title": "Bayes Factors",
      "topics": [
        "BFc"
      ]
    },
    {
      "page": "BFc.bpnme",
      "title": "Bayes Factors for a Bayesian circular mixed-effects model",
      "topics": [
        "BFc.bpnme"
      ]
    },
    {
      "page": "BFc.bpnr",
      "title": "Bayes Factors for a Bayesian circular regression model",
      "topics": [
        "BFc.bpnr"
      ]
    },
    {
      "page": "bpnme",
      "title": "Fit a Bayesian circular mixed-effects model",
      "topics": [
        "bpnme"
      ]
    },
    {
      "page": "bpnr",
      "title": "Fit a Bayesian circular regression model",
      "topics": [
        "bpnr"
      ]
    },
    {
      "page": "circ_coef",
      "title": "Compute circular coefficients from linear coefficients",
      "topics": [
        "circ_coef"
      ]
    },
    {
      "page": "circ_coef_rcpp",
      "title": "Compute circular coefficients",
      "topics": [
        "circ_coef_rcpp"
      ]
    },
    {
      "page": "coef_circ",
      "title": "Circular coefficients",
      "topics": [
        "coef_circ"
      ]
    },
    {
      "page": "coef_circ.bpnme",
      "title": "Obtain the circular coefficients of a Bayesian circular mixed-effects model",
      "topics": [
        "coef_circ.bpnme"
      ]
    },
    {
      "page": "coef_circ.bpnr",
      "title": "Obtain the circular coefficients of a Bayesian circular regression model",
      "topics": [
        "coef_circ.bpnr"
      ]
    },
    {
      "page": "coef_lin",
      "title": "Linear coefficients",
      "topics": [
        "coef_lin"
      ]
    },
    {
      "page": "coef_lin.bpnme",
      "title": "Obtain the linear coefficients of a Bayesian circular mixed-effects model",
      "topics": [
        "coef_lin.bpnme"
      ]
    },
    {
      "page": "coef_lin.bpnr",
      "title": "Obtain the linear coefficients of a Bayesian circular regression model",
      "topics": [
        "coef_lin.bpnr"
      ]
    },
    {
      "page": "coef_ran",
      "title": "Random effect variances",
      "topics": [
        "coef_ran"
      ]
    },
    {
      "page": "coef_ran.bpnme",
      "title": "Obtain random effect variances of a Bayesian circular mixed-effects model",
      "topics": [
        "coef_ran.bpnme"
      ]
    },
    {
      "page": "DIC_reg",
      "title": "Compute Model Fit Measures Regression Model",
      "topics": [
        "DIC_reg"
      ]
    },
    {
      "page": "eigen_val",
      "title": "Compute Eigenvalues",
      "topics": [
        "eigen_val"
      ]
    },
    {
      "page": "eigen_vec",
      "title": "Compute Eigenvectors",
      "topics": [
        "eigen_vec"
      ]
    },
    {
      "page": "fit",
      "title": "Model fit",
      "topics": [
        "fit"
      ]
    },
    {
      "page": "fit.bpnme",
      "title": "Model fit for a Bayesian circular mixed-effects model",
      "topics": [
        "fit.bpnme"
      ]
    },
    {
      "page": "fit.bpnr",
      "title": "Model fit for a Bayesian circular regression model",
      "topics": [
        "fit.bpnr"
      ]
    },
    {
      "page": "hmode",
      "title": "Estimate the mode by finding the highest posterior density interval",
      "topics": [
        "hmode"
      ]
    },
    {
      "page": "hmodeC",
      "title": "Estimate the mode by finding the highest posterior density interval",
      "topics": [
        "hmodeC"
      ]
    },
    {
      "page": "hmodeci",
      "title": "Find the highest density interval.",
      "topics": [
        "hmodeci"
      ]
    },
    {
      "page": "hmodeciC",
      "title": "Find the highest density interval of a circular variable",
      "topics": [
        "hmodeciC"
      ]
    },
    {
      "page": "hpd_est",
      "title": "Compute the 95 percent HPD of a vector of linear data",
      "topics": [
        "hpd_est"
      ]
    },
    {
      "page": "hpd_est_circ",
      "title": "Compute the 95 percent HPD of a vector of circular data",
      "topics": [
        "hpd_est_circ"
      ]
    },
    {
      "page": "lik_me",
      "title": "Compute the Likelihood of the PN distribution (mixed effects)",
      "topics": [
        "lik_me"
      ]
    },
    {
      "page": "lik_reg",
      "title": "Compute the Likelihood of the PN distribution (regression)",
      "topics": [
        "lik_reg"
      ]
    },
    {
      "page": "Maps",
      "title": "The geometry of human knowledge of navigation space.",
      "topics": [
        "Maps"
      ]
    },
    {
      "page": "mean_circ",
      "title": "Compute the mean of a vector of circular data",
      "topics": [
        "mean_circ"
      ]
    },
    {
      "page": "mmme",
      "title": "Create model matrices for a circular mixed-effects regression model",
      "topics": [
        "mmme"
      ]
    },
    {
      "page": "mmr",
      "title": "Create model matrices circular regression",
      "topics": [
        "mmr"
      ]
    },
    {
      "page": "mode_est",
      "title": "Compute the mode of a vector of linear data",
      "topics": [
        "mode_est"
      ]
    },
    {
      "page": "mode_est_circ",
      "title": "Compute the mode of a vector of circular data",
      "topics": [
        "mode_est_circ"
      ]
    },
    {
      "page": "Motor",
      "title": "Phase differences in hand flexion-extension movements.",
      "topics": [
        "Motor"
      ]
    },
    {
      "page": "mvrnorm_arma_eigen",
      "title": "Sample from a multivariate normal distribution",
      "topics": [
        "mvrnorm_arma_eigen"
      ]
    },
    {
      "page": "pnme",
      "title": "A Gibbs sampler for a projected normal mixed-effects model",
      "topics": [
        "pnme"
      ]
    },
    {
      "page": "pnr",
      "title": "A Gibbs sampler for a projected normal regression model",
      "topics": [
        "pnr"
      ]
    },
    {
      "page": "print.bpnme",
      "title": "Print output from a Bayesian circular mixed-effects model",
      "topics": [
        "print.bpnme"
      ]
    },
    {
      "page": "print.bpnr",
      "title": "Print output from a Bayesian circular regression model",
      "topics": [
        "print.bpnr"
      ]
    },
    {
      "page": "rho",
      "title": "Compute a mean resultant length",
      "topics": [
        "rho"
      ]
    },
    {
      "page": "rho_circ",
      "title": "Compute the mean resultant length of a vector of circular data",
      "topics": [
        "rho_circ"
      ]
    },
    {
      "page": "sd_circ",
      "title": "Compute the standard deviation of a vector of circular data",
      "topics": [
        "sd_circ"
      ]
    },
    {
      "page": "slice_rcpp",
      "title": "A slice sampler for the latent lengths r",
      "topics": [
        "slice_rcpp"
      ]
    },
    {
      "page": "theta_bar",
      "title": "Compute a mean direction",
      "topics": [
        "theta_bar"
      ]
    },
    {
      "page": "traceplot",
      "title": "Traceplots",
      "topics": [
        "traceplot"
      ]
    },
    {
      "page": "traceplot.bpnme",
      "title": "Traceplots for a Bayesian circular mixed-effects model",
      "topics": [
        "traceplot.bpnme"
      ]
    },
    {
      "page": "traceplot.bpnr",
      "title": "Traceplots for a Bayesian circular regression model",
      "topics": [
        "traceplot.bpnr"
      ]
    }
  ],
  "_readme": "https://github.com/joliencremers/bpnreg/raw/HEAD/README.md",
  "_rundeps": [
    "BH",
    "bit",
    "bit64",
    "cli",
    "clipr",
    "cpp11",
    "crayon",
    "forcats",
    "glue",
    "haven",
    "hms",
    "lifecycle",
    "magrittr",
    "pillar",
    "pkgconfig",
    "prettyunits",
    "progress",
    "R6",
    "Rcpp",
    "RcppArmadillo",
    "readr",
    "rlang",
    "tibble",
    "tidyselect",
    "tzdb",
    "utf8",
    "vctrs",
    "vroom",
    "withr"
  ],
  "_sysdeps": [
    {
      "shlib": "liblapack",
      "package": "libopenblas0-pthread",
      "source": "openblas",
      "version": "0.3.26+ds-1ubuntu0.1",
      "name": "openblas",
      "homepage": "https://www.openblas.net/",
      "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)"
    },
    {
      "shlib": "libblas",
      "package": "libopenblas0-pthread",
      "source": "openblas",
      "version": "0.3.26+ds-1ubuntu0.1",
      "name": "openblas",
      "homepage": "https://www.openblas.net/",
      "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)"
    },
    {
      "shlib": "libstdc++",
      "package": "libstdc++6",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "c++",
      "homepage": "http://gcc.gnu.org/",
      "description": "GNU Standard C++ Library v3"
    },
    {
      "shlib": "libgomp",
      "package": "libgomp1",
      "source": "gcc",
      "version": "14.2.0-4ubuntu2~24.04.1",
      "name": "openmp",
      "homepage": "http://gcc.gnu.org/",
      "description": "GCC OpenMP (GOMP) support library"
    }
  ],
  "_vignettes": [
    {
      "source": "FAQ.Rmd",
      "filename": "FAQ.html",
      "title": "FAQ",
      "engine": "knitr::rmarkdown",
      "headings": [
        "How to fit a circular regression model:",
        "How to fit a circular mixed effects model:",
        "How to specify interaction effects:",
        "How to format the input data:",
        "Are missing values allowed in the input data and how are missing values dealt with?",
        "How to scale the dependent variable:",
        "Can user-specified priors be used?",
        "Can multiple grouping/nesting factors be used?",
        "How to specify a seed:",
        "How to obtain model summaries:",
        "How to interpret the output of the coef_circ() function:",
        "How to obtain model fit statistics:",
        "How to obtain the raw posterior estimates:",
        "How to obtain random effect variances and individual random effects in circular mixed-effects models:",
        "How to obtain the estimated variance for different groups in a circular regression or circular mixed-effects models:",
        "References"
      ],
      "created": "2021-03-01 10:16:16",
      "modified": "2021-03-09 15:17:23",
      "commits": 5
    }
  ],
  "_score": 6.176091259055681,
  "_indexed": true,
  "_nocasepkg": "bpnreg",
  "_universes": [
    "joliencremers"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "2.0.3",
      "date": "2026-06-02T11:13:03.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "4a96e547bd68b4d7002daadff1ab05734b84eebfa2e54ed5f698b15e16117d7b",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "2.0.3",
      "date": "2026-06-02T11:13:05.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "174bd57a77651374c1999b6f1fa81da871a10f581eb4a39840c274853fa21ba7",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "2.0.3",
      "date": "2026-06-02T11:12:54.000Z",
      "distro": "noble",
      "arch": "aarch64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "7d75356390c5ebd64d860108f6bad5215e58c029ad01df21de398bc2adf82edb",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "2.0.3",
      "date": "2026-06-02T11:12:52.000Z",
      "distro": "noble",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "59664e1006d96c88126967d0c00e33ce2646dd1320cf42191e37977456e0c317",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "2.0.3",
      "date": "2026-06-02T11:14:40.000Z",
      "arch": "aarch64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "e0b9b62b575ed491ccf36480c5fb05ffe60f5732d076d2dc0d08d2502bc2e97d",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "2.0.3",
      "date": "2026-06-02T11:13:53.000Z",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "8b99acbfda7befcc0fa2ee5dea0e002196a96d124b17ae8a73e749306fb2d786",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "2.0.3",
      "date": "2026-06-02T11:12:21.000Z",
      "arch": "aarch64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "a9fe698e46f691fa3240645a97940e4dbfec884a3e2ec6e3ec2d8fc058d23580",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "2.0.3",
      "date": "2026-06-02T11:13:50.000Z",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "22db09a9c492329ab99b53a29a48ea9ea80f26fdd48bc190fe109825f6440a6f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "2.0.3",
      "date": "2026-06-02T11:12:47.000Z",
      "arch": "emscripten",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "f9b0dfabab22a7f1923e2d05dd1c86fd9d1b0a9e1f4f4087c07efec7c4faa1da",
      "status": "success",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "2.0.3",
      "date": "2026-06-02T11:12:23.000Z",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "86a11d7876480e0bbb72a6fb52d726e158287fcbc8690bc9c8d7a5e68e366111",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "2.0.3",
      "date": "2026-06-02T11:11:59.000Z",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "04506558ad2ccf1e5455d462f8f476105fa0ab527ffc8a92ee61ff547e062826",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "2.0.3",
      "date": "2026-06-02T11:12:02.000Z",
      "arch": "x86_64",
      "commit": "1d32f5e9ac89e992f28f71814ad2dbcd619aa85b",
      "fileid": "5c2a597b1d1ab6d0accf22ce4f38bbf79a650d3c85542179c0bdb49ef16d722f",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/joliencremers/actions/runs/26815668651"
    }
  ]
}