{
  "_id": "6a0f6414acfb0bcc41c5cac3",
  "Package": "tidyfit",
  "Type": "Package",
  "Title": "Regularized Linear Modeling with Tidy Data",
  "Date": "2025-04-29",
  "Version": "0.7.4",
  "Author": "Johann Pfitzinger [aut, cre]",
  "Authors@R": "person(given = \"Johann\", family = \"Pfitzinger\", role = c(\"aut\", \"cre\"), email = \"johann.pfitzinger@gmail.com\")",
  "Maintainer": "Johann Pfitzinger <johann.pfitzinger@gmail.com>",
  "Description": "An extension to the 'R' tidy data environment for\nautomated machine learning. The package allows fitting and\ncross validation of linear regression and classification\nalgorithms on grouped data.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.3.2",
  "URL": "https://tidyfit.residualmetrics.com,\nhttps://github.com/jpfitzinger/tidyfit",
  "Roxygen": "list(markdown=TRUE)",
  "VignetteBuilder": "knitr",
  "Config/testthat/edition": "3",
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://jpfitzinger.r-universe.dev",
  "Date/Publication": "2025-04-29 18:13:28 UTC",
  "RemoteUrl": "https://github.com/jpfitzinger/tidyfit",
  "RemoteRef": "HEAD",
  "RemoteSha": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-21 10:24:22 UTC",
    "User": "root"
  },
  "MD5sum": "bf7fbc8e975b1afb34be7a09d0485dea",
  "_user": "jpfitzinger",
  "_type": "src",
  "_file": "tidyfit_0.7.4.tar.gz",
  "_fileid": "9b6acb483cc3265233499389779ad143f55ca3a539f333f920fc3f411c97a845",
  "_filesize": 3002595,
  "_sha256": "9b6acb483cc3265233499389779ad143f55ca3a539f333f920fc3f411c97a845",
  "_created": "2026-05-21T10:24:22.000Z",
  "_published": "2026-05-21T19:59:16.938Z",
  "_distro": "noble",
  "_jobs": [
    {
      "job": 77257176829,
      "time": 211,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "ERROR",
      "artifact": "7133345950"
    },
    {
      "job": 77257177215,
      "time": 248,
      "config": "linux-release-x86_64",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7133358008"
    },
    {
      "job": 77257177108,
      "time": 142,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "ERROR",
      "artifact": "7133326931"
    },
    {
      "job": 77257176907,
      "time": 157,
      "config": "macos-release-arm64",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7133331644"
    },
    {
      "job": 77257176246,
      "time": 292,
      "config": "source",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7133275682"
    },
    {
      "job": 77257176185,
      "time": 168,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "7145868510"
    },
    {
      "job": 77257176777,
      "time": 177,
      "config": "windows-devel",
      "r": "4.7.0",
      "check": "WARNING",
      "artifact": "7133335225"
    },
    {
      "job": 77257176769,
      "time": 174,
      "config": "windows-oldrel",
      "r": "4.5.3",
      "check": "WARNING",
      "artifact": "7133333549"
    },
    {
      "job": 77257176743,
      "time": 166,
      "config": "windows-release",
      "r": "4.6.0",
      "check": "WARNING",
      "artifact": "7133330953"
    }
  ],
  "_buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/jpfitzinger/tidyfit",
  "_commit": {
    "id": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
    "author": "Johann Pfitzinger <johann.pfitzinger@gmail.com>",
    "committer": "Johann Pfitzinger <johann.pfitzinger@gmail.com>",
    "message": "shorten long-running examples\n",
    "time": 1745950408
  },
  "_maintainer": {
    "name": "Johann Pfitzinger",
    "email": "johann.pfitzinger@gmail.com",
    "login": "jpfitzinger",
    "description": "Machine learning enthusiast  ·  Data Scientist  ·  financial ML",
    "uuid": 18226483
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.1",
      "role": "Depends"
    },
    {
      "package": "broom",
      "role": "Imports"
    },
    {
      "package": "crayon",
      "role": "Imports"
    },
    {
      "package": "dials",
      "role": "Imports"
    },
    {
      "package": "dplyr",
      "role": "Imports"
    },
    {
      "package": "furrr",
      "role": "Imports"
    },
    {
      "package": "generics",
      "role": "Imports"
    },
    {
      "package": "MASS",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "progressr",
      "role": "Imports"
    },
    {
      "package": "purrr",
      "role": "Imports"
    },
    {
      "package": "rlang",
      "role": "Imports"
    },
    {
      "package": "rsample",
      "role": "Imports"
    },
    {
      "package": "stats",
      "role": "Imports"
    },
    {
      "package": "tibble",
      "role": "Imports"
    },
    {
      "package": "tidyr",
      "role": "Imports"
    },
    {
      "package": "utils",
      "role": "Imports"
    },
    {
      "package": "vctrs",
      "role": "Imports"
    },
    {
      "package": "yardstick",
      "role": "Imports"
    },
    {
      "package": "arm",
      "role": "Suggests"
    },
    {
      "package": "bestglm",
      "role": "Suggests"
    },
    {
      "package": "BMS",
      "role": "Suggests"
    },
    {
      "package": "BoomSpikeSlab",
      "role": "Suggests"
    },
    {
      "package": "CORElearn",
      "role": "Suggests"
    },
    {
      "package": "e1071",
      "role": "Suggests"
    },
    {
      "package": "gaselect",
      "role": "Suggests"
    },
    {
      "package": "gets",
      "role": "Suggests"
    },
    {
      "package": "gglasso",
      "role": "Suggests"
    },
    {
      "package": "ggplot2",
      "role": "Suggests"
    },
    {
      "package": "glmnet",
      "role": "Suggests"
    },
    {
      "package": "hfr",
      "role": "Suggests"
    },
    {
      "package": "iml",
      "role": "Suggests"
    },
    {
      "package": "kableExtra",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "lme4",
      "role": "Suggests"
    },
    {
      "package": "lmtest",
      "role": "Suggests"
    },
    {
      "package": "lubridate",
      "role": "Suggests"
    },
    {
      "package": "markdown",
      "role": "Suggests"
    },
    {
      "package": "mboost",
      "role": "Suggests"
    },
    {
      "package": "monomvn",
      "role": "Suggests"
    },
    {
      "package": "mRMRe",
      "role": "Suggests"
    },
    {
      "package": "MSwM",
      "role": "Suggests"
    },
    {
      "package": "nnet",
      "role": "Suggests"
    },
    {
      "package": "pls",
      "role": "Suggests"
    },
    {
      "package": "quantreg",
      "role": "Suggests"
    },
    {
      "package": "quantregForest",
      "role": "Suggests"
    },
    {
      "package": "randomForest",
      "role": "Suggests"
    },
    {
      "package": "sandwich",
      "role": "Suggests"
    },
    {
      "package": "sensitivity",
      "role": "Suggests"
    },
    {
      "package": "shrinkTVP",
      "role": "Suggests"
    },
    {
      "package": "stringr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "version": ">= 3.0.0",
      "role": "Suggests"
    }
  ],
  "_owner": "jpfitzinger",
  "_selfowned": true,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_topics": [
    "auto-ml",
    "classification",
    "machine-learning",
    "regression",
    "tidyverse"
  ],
  "_stars": 17,
  "_contributors": [
    {
      "user": "jpfitzinger",
      "count": 529,
      "uuid": 18226483
    }
  ],
  "_userbio": {
    "uuid": 18226483,
    "type": "user",
    "name": "Johann Pfitzinger",
    "description": "Machine learning enthusiast  ·  Data Scientist  ·  financial ML"
  },
  "_downloads": {
    "count": 312,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/tidyfit"
  },
  "_devurl": "https://github.com/jpfitzinger/tidyfit",
  "_pkgdown": "https://tidyfit.residualmetrics.com",
  "_searchresults": 41,
  "_rbuild": "4.6.0",
  "_assets": [
    "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",
    "extra/tidyfit.html",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/jpfitzinger/tidyfit",
  "_realowner": "jpfitzinger",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.5.1",
      "date": "2022-10-31"
    },
    {
      "version": "0.6.0",
      "date": "2022-11-25"
    },
    {
      "version": "0.6.1",
      "date": "2023-01-21"
    },
    {
      "version": "0.6.2",
      "date": "2023-02-19"
    },
    {
      "version": "0.6.3",
      "date": "2023-03-15"
    },
    {
      "version": "0.6.4",
      "date": "2023-05-20"
    },
    {
      "version": "0.6.5",
      "date": "2023-11-21"
    },
    {
      "version": "0.7.0",
      "date": "2024-02-26"
    },
    {
      "version": "0.7.1",
      "date": "2024-03-23"
    },
    {
      "version": "0.7.2",
      "date": "2024-10-03"
    },
    {
      "version": "0.7.3",
      "date": "2025-01-17"
    },
    {
      "version": "0.7.4",
      "date": "2025-04-29"
    }
  ],
  "_exports": [
    "classify",
    "explain",
    "get_model",
    "get_tidyFit",
    "m",
    "regress"
  ],
  "_datasets": [
    {
      "name": "Factor_Industry_Returns",
      "title": "Industry-Factor Returns Data Set",
      "object": "Factor_Industry_Returns",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Date",
        "Industry",
        "Return",
        "Mkt-RF",
        "SMB",
        "HML",
        "RMW",
        "CMA",
        "RF"
      ],
      "rows": 7080,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "dot-fit.adalasso",
      "title": "Adaptive Lasso regression or classification for 'tidyfit'",
      "topics": [
        ".fit.adalasso"
      ]
    },
    {
      "page": "dot-fit.anova",
      "title": "ANOVA for 'tidyfit'",
      "topics": [
        ".fit.anova"
      ]
    },
    {
      "page": "dot-fit.bayes",
      "title": "Bayesian generalized linear regression for 'tidyfit'",
      "topics": [
        ".fit.bayes"
      ]
    },
    {
      "page": "dot-fit.blasso",
      "title": "Bayesian Lasso regression for 'tidyfit'",
      "topics": [
        ".fit.blasso"
      ]
    },
    {
      "page": "dot-fit.bma",
      "title": "Bayesian model averaging for 'tidyfit'",
      "topics": [
        ".fit.bma"
      ]
    },
    {
      "page": "dot-fit.boost",
      "title": "Gradient boosting regression for 'tidyfit'",
      "topics": [
        ".fit.boost"
      ]
    },
    {
      "page": "dot-fit.bridge",
      "title": "Bayesian ridge regression for 'tidyfit'",
      "topics": [
        ".fit.bridge"
      ]
    },
    {
      "page": "dot-fit.chisq",
      "title": "Pearson's Chi-squared test for 'tidyfit'",
      "topics": [
        ".fit.chisq"
      ]
    },
    {
      "page": "dot-fit.cor",
      "title": "Pearson's correlation for 'tidyfit'",
      "topics": [
        ".fit.cor"
      ]
    },
    {
      "page": "dot-fit.enet",
      "title": "ElasticNet regression or classification for 'tidyfit'",
      "topics": [
        ".fit.enet"
      ]
    },
    {
      "page": "dot-fit.genetic",
      "title": "Genetic algorithm with linear regression fitness evaluator for 'tidyfit'",
      "topics": [
        ".fit.genetic"
      ]
    },
    {
      "page": "dot-fit.gets",
      "title": "General-to-specific regression for 'tidyfit'",
      "topics": [
        ".fit.gets"
      ]
    },
    {
      "page": "dot-fit.glm",
      "title": "Generalized linear regression for 'tidyfit'",
      "topics": [
        ".fit.glm"
      ]
    },
    {
      "page": "dot-fit.glmm",
      "title": "Generalized linear mixed-effects model for 'tidyfit'",
      "topics": [
        ".fit.glmm"
      ]
    },
    {
      "page": "dot-fit.group_lasso",
      "title": "Grouped Lasso regression and classification for 'tidyfit'",
      "topics": [
        ".fit.group_lasso"
      ]
    },
    {
      "page": "dot-fit.hfr",
      "title": "Hierarchical feature regression for 'tidyfit'",
      "topics": [
        ".fit.hfr"
      ]
    },
    {
      "page": "dot-fit.lasso",
      "title": "Lasso regression and classification for 'tidyfit'",
      "topics": [
        ".fit.lasso"
      ]
    },
    {
      "page": "dot-fit.lm",
      "title": "Linear regression for 'tidyfit'",
      "topics": [
        ".fit.lm"
      ]
    },
    {
      "page": "dot-fit.mrmr",
      "title": "Minimum redundancy, maximum relevance feature selection for 'tidyfit'",
      "topics": [
        ".fit.mrmr"
      ]
    },
    {
      "page": "dot-fit.mslm",
      "title": "Markov-Switching Regression for 'tidyfit'",
      "topics": [
        ".fit.mslm"
      ]
    },
    {
      "page": "dot-fit.nnet",
      "title": "Neural Network regression for 'tidyfit'",
      "topics": [
        ".fit.nnet"
      ]
    },
    {
      "page": "dot-fit.pcr",
      "title": "Principal Components Regression for 'tidyfit'",
      "topics": [
        ".fit.pcr"
      ]
    },
    {
      "page": "dot-fit.plsr",
      "title": "Partial Least Squares Regression for 'tidyfit'",
      "topics": [
        ".fit.plsr"
      ]
    },
    {
      "page": "dot-fit.quantile",
      "title": "Quantile regression for 'tidyfit'",
      "topics": [
        ".fit.quantile"
      ]
    },
    {
      "page": "dot-fit.quantile_rf",
      "title": "Quantile regression forest for 'tidyfit'",
      "topics": [
        ".fit.quantile_rf"
      ]
    },
    {
      "page": "dot-fit.relief",
      "title": "ReliefF and RReliefF feature selection algorithm for 'tidyfit'",
      "topics": [
        ".fit.relief"
      ]
    },
    {
      "page": "dot-fit.rf",
      "title": "Random Forest regression or classification for 'tidyfit'",
      "topics": [
        ".fit.rf"
      ]
    },
    {
      "page": "dot-fit.ridge",
      "title": "Ridge regression and classification for 'tidyfit'",
      "topics": [
        ".fit.ridge"
      ]
    },
    {
      "page": "dot-fit.robust",
      "title": "Robust regression for 'tidyfit'",
      "topics": [
        ".fit.robust"
      ]
    },
    {
      "page": "dot-fit.spikeslab",
      "title": "Bayesian Spike and Slab regression or classification for 'tidyfit'",
      "topics": [
        ".fit.spikeslab"
      ]
    },
    {
      "page": "dot-fit.subset",
      "title": "Best subset regression and classification for 'tidyfit'",
      "topics": [
        ".fit.subset"
      ]
    },
    {
      "page": "dot-fit.svm",
      "title": "Support vector regression or classification for 'tidyfit'",
      "topics": [
        ".fit.svm"
      ]
    },
    {
      "page": "dot-fit.tvp",
      "title": "Bayesian Time-Varying Regression for 'tidyfit'",
      "topics": [
        ".fit.tvp"
      ]
    },
    {
      "page": "classify",
      "title": "Classification on tidy data",
      "topics": [
        "classify"
      ]
    },
    {
      "page": "coef.tidyfit.models",
      "title": "Extract coefficients from a 'tidyfit.models' frame",
      "topics": [
        "coef.tidyfit.models"
      ]
    },
    {
      "page": "explain",
      "title": "An interface for variable importance measures for a fitted tidyfit.models frames",
      "topics": [
        "explain"
      ]
    },
    {
      "page": "explain.tidyfit.models",
      "title": "An interface for variable importance measures for a fitted tidyfit.models frames",
      "topics": [
        "explain.tidyfit.models"
      ]
    },
    {
      "page": "Factor_Industry_Returns",
      "title": "Industry-Factor Returns Data Set",
      "topics": [
        "Factor_Industry_Returns"
      ]
    },
    {
      "page": "fitted.tidyfit.models",
      "title": "Obtain fitted values from models in a 'tidyfit.models' frame",
      "topics": [
        "fitted.tidyfit.models"
      ]
    },
    {
      "page": "get_model",
      "title": "Get a fitted model from a tidyfit.models frame",
      "topics": [
        "get_model"
      ]
    },
    {
      "page": "get_tidyFit",
      "title": "Get a tidyFit model from a tidyfit.models frame",
      "topics": [
        "get_tidyFit"
      ]
    },
    {
      "page": "m",
      "title": "Generic model wrapper for 'tidyfit'",
      "topics": [
        "m"
      ]
    },
    {
      "page": "predict.tidyfit.models",
      "title": "Predict using a 'tidyfit.models' frame",
      "topics": [
        "predict.tidyfit.models"
      ]
    },
    {
      "page": "regress",
      "title": "Linear regression on tidy data",
      "topics": [
        "regress"
      ]
    },
    {
      "page": "residuals.tidyfit.models",
      "title": "Obtain residuals from models in a 'tidyfit.models' frame",
      "topics": [
        "residuals.tidyfit.models"
      ]
    }
  ],
  "_pkglogo": "https://github.com/jpfitzinger/tidyfit/raw/HEAD/man/figures/logo.png",
  "_readme": "https://github.com/jpfitzinger/tidyfit/raw/HEAD/README.md",
  "_rundeps": [
    "backports",
    "broom",
    "cli",
    "codetools",
    "cpp11",
    "crayon",
    "dials",
    "DiceDesign",
    "digest",
    "dplyr",
    "farver",
    "furrr",
    "future",
    "generics",
    "globals",
    "glue",
    "hardhat",
    "labeling",
    "lifecycle",
    "listenv",
    "magrittr",
    "MASS",
    "parallelly",
    "pillar",
    "pkgconfig",
    "progressr",
    "purrr",
    "R6",
    "RColorBrewer",
    "rlang",
    "rsample",
    "scales",
    "sfd",
    "slider",
    "sparsevctrs",
    "stringi",
    "stringr",
    "tibble",
    "tidyr",
    "tidyselect",
    "utf8",
    "vctrs",
    "viridisLite",
    "warp",
    "withr",
    "yardstick"
  ],
  "_vignettes": [
    {
      "source": "Accessing_Fitted_Model_Objects.Rmd",
      "filename": "Accessing_Fitted_Model_Objects.html",
      "title": "Accessing Fitted Model Objects",
      "engine": "knitr::rmarkdown",
      "headings": [],
      "created": "2022-08-27 14:54:25",
      "modified": "2025-04-29 17:44:04",
      "commits": 8
    },
    {
      "source": "Bootstrapping_Confidence_Intervals.Rmd",
      "filename": "Bootstrapping_Confidence_Intervals.html",
      "title": "Bootstrapping Confidence Intervals",
      "engine": "knitr::knitr",
      "headings": [
        "Fit the model",
        "Plot the results",
        "Comparing to built-in jackknife procedure"
      ],
      "created": "2022-08-27 14:54:25",
      "modified": "2025-04-29 17:20:31",
      "commits": 7
    },
    {
      "source": "Feature_Selection.Rmd",
      "filename": "Feature_Selection.html",
      "title": "Feature Selection",
      "engine": "knitr::knitr",
      "headings": [
        "Feature selection algorithms",
        "Filter methods",
        "Wrapper methods",
        "Embedded methods",
        "Extracting the top models"
      ],
      "created": "2022-11-23 05:44:00",
      "modified": "2025-04-29 17:20:31",
      "commits": 6
    },
    {
      "source": "Flowchart.Rmd",
      "filename": "Flowchart.html",
      "title": "Flowchart",
      "engine": "knitr::rmarkdown",
      "headings": [],
      "created": "2022-10-22 16:31:17",
      "modified": "2022-10-22 16:31:17",
      "commits": 1
    },
    {
      "source": "Multinomial_Classification.Rmd",
      "filename": "Multinomial_Classification.html",
      "title": "Multinomial Classification",
      "engine": "knitr::knitr",
      "headings": [
        "Penalized classification algorithms to predict Species"
      ],
      "created": "2022-08-20 07:14:12",
      "modified": "2025-04-29 17:20:31",
      "commits": 8
    },
    {
      "source": "Predicting_Boston_House_Prices.Rmd",
      "filename": "Predicting_Boston_House_Prices.html",
      "title": "Predicting Boston House Prices",
      "engine": "knitr::rmarkdown",
      "headings": [
        "A simple regression",
        "Regularized regression estimators",
        "A glimpse at the backend"
      ],
      "created": "2022-08-20 07:14:12",
      "modified": "2025-04-29 17:20:31",
      "commits": 14
    },
    {
      "source": "Rolling_Window_Time_Series_Regression.Rmd",
      "filename": "Rolling_Window_Time_Series_Regression.html",
      "title": "Rolling Window Time Series Regression",
      "engine": "knitr::knitr",
      "headings": [],
      "created": "2022-08-26 18:36:28",
      "modified": "2025-04-29 17:20:31",
      "commits": 8
    },
    {
      "source": "Time-varying_parameters_vs_rolling_windows.Rmd",
      "filename": "Time-varying_parameters_vs_rolling_windows.html",
      "title": "Time-varying parameters vs. rolling windows",
      "engine": "knitr::knitr",
      "headings": [
        "Load the data",
        "Model fitting",
        "Plotting the results"
      ],
      "created": "2022-08-27 14:54:25",
      "modified": "2025-04-29 17:20:31",
      "commits": 7
    }
  ],
  "_score": 6.445292769425972,
  "_indexed": true,
  "_nocasepkg": "tidyfit",
  "_universes": [
    "jpfitzinger"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.7.4",
      "date": "2026-05-21T10:27:20.000Z",
      "distro": "noble",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "f837efb9d283b98f9f5f2979d30e39e944b5c6dfe321557393a92bb5ab3cf1d7",
      "status": "failure",
      "check": "ERROR",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.6.0",
      "os": "linux",
      "version": "0.7.4",
      "date": "2026-05-21T10:27:45.000Z",
      "distro": "noble",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "6f0512aca158517cb8a97fdb8d67b8438dbf58700c454503c8412bf157977515",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "0.7.4",
      "date": "2026-05-21T10:26:35.000Z",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "bfecafb5f1156fbd399927f1ef440c2646c37cf4f01b6619c1bd03e8bf4c1373",
      "status": "failure",
      "check": "ERROR",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.6.0",
      "os": "mac",
      "version": "0.7.4",
      "date": "2026-05-21T10:26:30.000Z",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "5bce32bbdd599a6a33957afcee7433b49e30710bc42c7bf4354f0677428afd9d",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.7.4",
      "date": "2026-05-21T19:59:01.000Z",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "ce432c54de9892c2bacae3ca2a01d5c5dc9f8b83ce95881ae9152a7455b3b09e",
      "status": "success",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.7.4",
      "date": "2026-05-21T10:26:12.000Z",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "b8d439ea017f6572b58ce13c8bf6bed976fbc807ab9153e232ec5592000eed26",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "0.7.4",
      "date": "2026-05-21T10:26:07.000Z",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "b8db29c1e820af093f061dddc23b45e859d6d443229553adda478718ca8a681d",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    },
    {
      "r": "4.6.0",
      "os": "win",
      "version": "0.7.4",
      "date": "2026-05-21T10:25:57.000Z",
      "commit": "3d9d0129b87231020d6b7eb27b45316dabfc43fa",
      "fileid": "c5d7c0ebd9c383137d49e2a7a90a97fcf1b42c462d80fc1562c7118c6b78ca91",
      "status": "success",
      "check": "WARNING",
      "buildurl": "https://github.com/r-universe/jpfitzinger/actions/runs/26220046743"
    }
  ]
}