{
  "_id": "6a17f68cacfb0bcc41da89c3",
  "Package": "metrica",
  "Title": "Prediction Performance Metrics",
  "Version": "2.1.0",
  "Date": "2024-06-30",
  "Authors@R": "c(\nperson(\"Adrian A.\", \"Correndo\", email = \"acorrend@uoguelph.ca\", role = c(\"aut\", \"cre\", \"cph\"), comment = c(ORCID = \"0000-0002-4172-289X\")),\nperson(\"Luiz H.\", \"Moro Rosso\", email = \"lhmrosso@ksu.edu\", role = \"aut\", comment = c(ORCID = \"0000-0002-8642-911X\")),\nperson(\"Rai\", \"Schwalbert\", email = \"rai.schwalbert@hotmail.com\", role = \"aut\", comment = c(ORCID = \"0000-0001-8488-7507\")),\nperson(\"Carlos\", \"Hernandez\", email = \"carlosh92@ksu.edu\", role = \"aut\", comment = c(ORCID = \"0000-0001-5171-2516\")),\nperson(\"Leonardo M.\", \"Bastos\", email = \"leonardombastos@gmail.com\", role = \"aut\", comment = c(ORCID = \"0000-0001-8958-6527\")),\nperson(\"Luciana\", \"Nieto\", email = \"lnieto@ksu.edu\", comment = c(ORCID = \"0000-0002-7172-0799\"), role = \"aut\"),\nperson(\"Dean\", \"Holzworth\", email = \"dean.holzworth@csiro.au\", role = \"aut\"),\nperson(\"Ignacio A.\", \"Ciampitti\", email = \"ciampitti@ksu.edu\", role = \"aut\", comment = c(ORCID = \"0000-0001-9619-5129\")))",
  "Description": "A compilation of more than 80 functions designed to\nquantitatively and visually evaluate prediction performance of\nregression (continuous variables) and classification\n(categorical variables) of point-forecast models (e.g. APSIM,\nDSSAT, DNDC, supervised Machine Learning). For regression, it\nincludes functions to generate plots (scatter, tiles, density,\n& Bland-Altman plot), and to estimate error metrics (e.g. MBE,\nMAE, RMSE), error decomposition (e.g. lack of\naccuracy-precision), model efficiency (e.g. NSE, E1, KGE),\nindices of agreement (e.g. d, RAC), goodness of fit (e.g. r,\nR2), adjusted correlation coefficients (e.g. CCC, dcorr),\nsymmetric regression coefficients (intercept, slope), and mean\nabsolute scaled error (MASE) for time series predictions. For\nclassification (binomial and multinomial), it offers functions\nto generate and plot confusion matrices, and to estimate\nperformance metrics such as accuracy, precision, recall,\nspecificity, F-score, Cohen's Kappa, G-mean, and many more. For\nmore details visit the vignettes\n<https://adriancorrendo.github.io/metrica/>.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.3.1",
  "Config/testthat/edition": "3",
  "VignetteBuilder": "knitr",
  "URL": "https://adriancorrendo.github.io/metrica/",
  "BugReports": "https://github.com/adriancorrendo/metrica/issues",
  "Config/pak/sysreqs": "libgsl0-dev libicu-dev",
  "Repository": "https://adriancorrendo.r-universe.dev",
  "Date/Publication": "2024-06-30 13:05:52 UTC",
  "RemoteUrl": "https://github.com/adriancorrendo/metrica",
  "RemoteRef": "HEAD",
  "RemoteSha": "f01f1cf5884af1b3607834d66761a316cdc83c0c",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-28 07:56:36 UTC",
    "User": "root"
  },
  "Author": "Adrian A. Correndo [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0002-4172-289X>),\nLuiz H. Moro Rosso [aut] (ORCID:\n<https://orcid.org/0000-0002-8642-911X>),\nRai Schwalbert [aut] (ORCID: <https://orcid.org/0000-0001-8488-7507>),\nCarlos Hernandez [aut] (ORCID: <https://orcid.org/0000-0001-5171-2516>),\nLeonardo M. Bastos [aut] (ORCID:\n<https://orcid.org/0000-0001-8958-6527>),\nLuciana Nieto [aut] (ORCID: <https://orcid.org/0000-0002-7172-0799>),\nDean Holzworth [aut],\nIgnacio A. Ciampitti [aut] (ORCID:\n<https://orcid.org/0000-0001-9619-5129>)",
  "Maintainer": "Adrian A. Correndo <acorrend@uoguelph.ca>",
  "MD5sum": "ff74d8d0e1a767ac3017134a9a50c36d",
  "_user": "adriancorrendo",
  "_type": "src",
  "_file": "metrica_2.1.0.tar.gz",
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  "_created": "2026-05-28T07:56:36.000Z",
  "_published": "2026-05-28T08:02:20.547Z",
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  "_exports": [
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    "accuracy",
    "agf",
    "AUC_roc",
    "B0_sma",
    "B1_sma",
    "balacc",
    "bland_altman_plot",
    "bmi",
    "CCC",
    "confusion_matrix",
    "csi",
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    "d1r",
    "dcorr",
    "deltap",
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    "Erel",
    "error_rate",
    "FDR",
    "fmi",
    "FNR",
    "FOR",
    "FPR",
    "fscore",
    "gmean",
    "hitrate",
    "import_apsim_db",
    "import_apsim_out",
    "iqRMSE",
    "jaccardindex",
    "jindex",
    "KGE",
    "khat",
    "lambda",
    "LCS",
    "MAE",
    "MAPE",
    "MASE",
    "MBE",
    "mcc",
    "metrics_summary",
    "MIC",
    "mk",
    "MLA",
    "MLP",
    "MSE",
    "negLr",
    "npv",
    "NSE",
    "p4",
    "PAB",
    "PBE",
    "phi_coef",
    "PLA",
    "PLP",
    "posLr",
    "PPB",
    "ppv",
    "precision",
    "preval",
    "preval_t",
    "r",
    "R2",
    "RAC",
    "RAE",
    "recall",
    "RMAE",
    "RMLA",
    "RMLP",
    "RMSE",
    "RRMSE",
    "RSE",
    "RSR",
    "RSS",
    "SB",
    "scatter_plot",
    "SDSD",
    "selectivity",
    "sensitivity",
    "SMAPE",
    "specificity",
    "tiles_plot",
    "TNR",
    "TPR",
    "TSS",
    "Ub",
    "Uc",
    "Ue",
    "uSD",
    "var_u",
    "Xa"
  ],
  "_datasets": [
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      "name": "barley",
      "title": "Barley grain number",
      "object": "barley",
      "class": [
        "data.frame"
      ],
      "fields": [
        "pred",
        "obs"
      ],
      "rows": 69,
      "table": true,
      "tojson": true
    },
    {
      "name": "chickpea",
      "title": "Chickpea dry mass",
      "object": "chickpea",
      "class": [
        "data.frame"
      ],
      "fields": [
        "pred",
        "obs"
      ],
      "rows": 39,
      "table": true,
      "tojson": true
    },
    {
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      "title": "Binary Land Cover Data",
      "object": "land_cover",
      "class": [
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      ],
      "fields": [
        "actual",
        "predicted"
      ],
      "rows": 285,
      "table": true,
      "tojson": true
    },
    {
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      "title": "Multi Class Phenology",
      "object": "maize_phenology",
      "class": [
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      ],
      "fields": [
        "actual",
        "predicted"
      ],
      "rows": 103,
      "table": true,
      "tojson": true
    },
    {
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      "title": "Sorghum grain number",
      "object": "sorghum",
      "class": [
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      ],
      "fields": [
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        "obs"
      ],
      "rows": 36,
      "table": true,
      "tojson": true
    },
    {
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      "object": "wheat",
      "class": [
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      "fields": [
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        "obs"
      ],
      "rows": 137,
      "table": true,
      "tojson": true
    }
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  "_help": [
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      "page": "AC",
      "title": "Ji and Gallo's Agreement Coefficient (AC)",
      "topics": [
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      ]
    },
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      "title": "Accuracy",
      "topics": [
        "accuracy"
      ]
    },
    {
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      "title": "Adjusted F-score",
      "topics": [
        "agf"
      ]
    },
    {
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      "title": "Area Under the ROC Curve",
      "topics": [
        "AUC_roc"
      ]
    },
    {
      "page": "B0_sma",
      "title": "Intercept of standardized major axis regression (SMA).",
      "topics": [
        "B0_sma"
      ]
    },
    {
      "page": "B1_sma",
      "title": "Slope of standardized major axis regression (SMA).",
      "topics": [
        "B1_sma"
      ]
    },
    {
      "page": "balacc",
      "title": "Balanced Accuracy",
      "topics": [
        "balacc"
      ]
    },
    {
      "page": "barley",
      "title": "Barley grain number",
      "topics": [
        "barley"
      ]
    },
    {
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      "title": "Bland-Altman plot",
      "topics": [
        "bland_altman_plot"
      ]
    },
    {
      "page": "bmi",
      "title": "Bookmaker Informedness",
      "topics": [
        "bmi",
        "jindex"
      ]
    },
    {
      "page": "CCC",
      "title": "Concordance correlation coefficient (CCC)",
      "topics": [
        "CCC"
      ]
    },
    {
      "page": "chickpea",
      "title": "Chickpea dry mass",
      "topics": [
        "chickpea"
      ]
    },
    {
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      "title": "Confusion Matrix",
      "topics": [
        "confusion_matrix"
      ]
    },
    {
      "page": "csi",
      "title": "Critical Success Index | Jaccard's Index",
      "topics": [
        "csi",
        "jaccardindex"
      ]
    },
    {
      "page": "d",
      "title": "Willmott's Index of Agreement (d)",
      "topics": [
        "d"
      ]
    },
    {
      "page": "d1",
      "title": "Modified Index of Agreement (d1).",
      "topics": [
        "d1"
      ]
    },
    {
      "page": "d1r",
      "title": "Refined Index of Agreement (d1).",
      "topics": [
        "d1r"
      ]
    },
    {
      "page": "dcorr",
      "title": "Distance Correlation",
      "topics": [
        "dcorr"
      ]
    },
    {
      "page": "deltap",
      "title": "deltaP or Markedness",
      "topics": [
        "deltap",
        "mk"
      ]
    },
    {
      "page": "density_plot",
      "title": "Density plot of predicted and observed values",
      "topics": [
        "density_plot"
      ]
    },
    {
      "page": "E1",
      "title": "Absolute Model Efficiency (E1)",
      "topics": [
        "E1"
      ]
    },
    {
      "page": "Erel",
      "title": "Relative Model Efficiency (Erel)",
      "topics": [
        "Erel"
      ]
    },
    {
      "page": "error_rate",
      "title": "Error rate",
      "topics": [
        "error_rate"
      ]
    },
    {
      "page": "fmi",
      "title": "Fowlkes-Mallows Index",
      "topics": [
        "fmi"
      ]
    },
    {
      "page": "fscore",
      "title": "F-score",
      "topics": [
        "fscore"
      ]
    },
    {
      "page": "gmean",
      "title": "Geometric Mean",
      "topics": [
        "gmean"
      ]
    },
    {
      "page": "import_apsim_db",
      "title": "Import SQLite databases generated by APSIM NextGen",
      "topics": [
        "import_apsim_db"
      ]
    },
    {
      "page": "import_apsim_out",
      "title": "import_apsim_out",
      "topics": [
        "import_apsim_out"
      ]
    },
    {
      "page": "iqRMSE",
      "title": "Inter-Quartile Root Mean Squared Error",
      "topics": [
        "iqRMSE"
      ]
    },
    {
      "page": "KGE",
      "title": "Kling-Gupta Model Efficiency (KGE).",
      "topics": [
        "KGE"
      ]
    },
    {
      "page": "khat",
      "title": "K-hat (Cohen's Kappa Coefficient)",
      "topics": [
        "khat"
      ]
    },
    {
      "page": "lambda",
      "title": "Duveiller's Agreement Coefficient",
      "topics": [
        "lambda"
      ]
    },
    {
      "page": "land_cover",
      "title": "Binary Land Cover Data",
      "topics": [
        "land_cover"
      ]
    },
    {
      "page": "LCS",
      "title": "Lack of Correlation (LCS)",
      "topics": [
        "LCS"
      ]
    },
    {
      "page": "likelihood_ratios",
      "title": "Likelihood Ratios (Classification)",
      "topics": [
        "dor",
        "likelihood_ratios",
        "negLr",
        "posLr"
      ]
    },
    {
      "page": "MAE",
      "title": "Mean Absolute Error (MAE)",
      "topics": [
        "MAE"
      ]
    },
    {
      "page": "maize_phenology",
      "title": "Multi Class Phenology",
      "topics": [
        "maize_phenology"
      ]
    },
    {
      "page": "MAPE",
      "title": "Mean Absolute Percentage Error (MAPE)",
      "topics": [
        "MAPE"
      ]
    },
    {
      "page": "MASE",
      "title": "Mean Absolute Scaled Error (MASE)",
      "topics": [
        "MASE"
      ]
    },
    {
      "page": "MBE",
      "title": "Mean Bias Error (MBE)",
      "topics": [
        "MBE"
      ]
    },
    {
      "page": "mcc",
      "title": "Matthews Correlation Coefficient | Phi Coefficient",
      "topics": [
        "mcc",
        "phi_coef"
      ]
    },
    {
      "page": "metrics_summary",
      "title": "Prediction Performance Summary",
      "topics": [
        "metrics_summary"
      ]
    },
    {
      "page": "MIC",
      "title": "Maximal Information Coefficient",
      "topics": [
        "MIC"
      ]
    },
    {
      "page": "MLA",
      "title": "Mean Lack of Accuracy (MLA)",
      "topics": [
        "MLA"
      ]
    },
    {
      "page": "MLP",
      "title": "Mean Lack of Precision (MLP)",
      "topics": [
        "MLP"
      ]
    },
    {
      "page": "MSE",
      "title": "Mean Squared Error (MSE)",
      "topics": [
        "MSE"
      ]
    },
    {
      "page": "npv",
      "title": "Negative Predictive Value",
      "topics": [
        "FOR",
        "npv"
      ]
    },
    {
      "page": "NSE",
      "title": "Nash-Sutcliffe Model Efficiency (NSE)",
      "topics": [
        "NSE"
      ]
    },
    {
      "page": "p4",
      "title": "P4-metric",
      "topics": [
        "p4"
      ]
    },
    {
      "page": "PAB",
      "title": "Percentage Additive Bias (PAB)",
      "topics": [
        "PAB"
      ]
    },
    {
      "page": "PBE",
      "title": "Percentage Bias Error (PBE).",
      "topics": [
        "PBE"
      ]
    },
    {
      "page": "PLA",
      "title": "Percentage Lack of Accuracy (PLA)",
      "topics": [
        "PLA"
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    },
    {
      "page": "PLP",
      "title": "Percentage Lack of Precision (PLP)",
      "topics": [
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      ]
    },
    {
      "page": "PPB",
      "title": "Percentage Proportional Bias (PPB)",
      "topics": [
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    },
    {
      "page": "precision",
      "title": "Precision | Positive Predictive Value",
      "topics": [
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        "ppv",
        "precision"
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    },
    {
      "page": "prevalence",
      "title": "Prevalence",
      "topics": [
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        "prevalence",
        "preval_t"
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    },
    {
      "page": "r",
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      "topics": [
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      ]
    },
    {
      "page": "R2",
      "title": "Coefficient of determination (R2).",
      "topics": [
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      ]
    },
    {
      "page": "RAC",
      "title": "Robinson's Agreement Coefficient (RAC).",
      "topics": [
        "RAC"
      ]
    },
    {
      "page": "RAE",
      "title": "Relative Absolute Error (RAE)",
      "topics": [
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      ]
    },
    {
      "page": "recall",
      "title": "Recall | Sensitivity | True Positive Rate | Hit rate",
      "topics": [
        "FNR",
        "hitrate",
        "recall",
        "sensitivity",
        "TPR"
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    },
    {
      "page": "RMAE",
      "title": "Relative Mean Absolute Error (RMAE)",
      "topics": [
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      ]
    },
    {
      "page": "RMLA",
      "title": "Root Mean Lack of Accuracy (RMLA)",
      "topics": [
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    },
    {
      "page": "RMLP",
      "title": "Root Mean Lack of Precision (RMLP)",
      "topics": [
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    },
    {
      "page": "RMSE",
      "title": "Root Mean Squared Error (RMSE)",
      "topics": [
        "RMSE"
      ]
    },
    {
      "page": "RRMSE",
      "title": "Relative Root Mean Squared Error (RMSE)",
      "topics": [
        "RRMSE"
      ]
    },
    {
      "page": "RSE",
      "title": "Relative Squared Error (RSE)",
      "topics": [
        "RSE"
      ]
    },
    {
      "page": "RSR",
      "title": "Root Mean Standard Deviation Ratio (RSR)",
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      ]
    },
    {
      "page": "RSS",
      "title": "Residual Sum of Squares (RSS)",
      "topics": [
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      ]
    },
    {
      "page": "SB",
      "title": "Squared bias (SB)",
      "topics": [
        "SB"
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    },
    {
      "page": "scatter_plot",
      "title": "Scatter plot of predicted and observed values",
      "topics": [
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      ]
    },
    {
      "page": "SDSD",
      "title": "Squared difference between standard deviations (SDSD)",
      "topics": [
        "SDSD"
      ]
    },
    {
      "page": "SMAPE",
      "title": "Symmetric Mean Absolute Percentage Error (SMAPE).",
      "topics": [
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      ]
    },
    {
      "page": "sorghum",
      "title": "Sorghum grain number",
      "topics": [
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      ]
    },
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      "page": "specificity",
      "title": "Specificity | Selectivity | True Negative Rate",
      "topics": [
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        "selectivity",
        "specificity",
        "TNR"
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    },
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      "page": "tiles_plot",
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      "page": "TSS",
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      "page": "Ub",
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      "page": "uSD",
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      "page": "wheat",
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