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  "Title": "Missing Value Imputation using Random Forest for Prediction\nSettings",
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  "Date": "2025-05-23",
  "Authors@R": "c(\nperson(\"Elena\", \"Albu\", , \"elenaa.albu@gmail.com\", c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2602-0918\", funding = \"KU Leuven\"))\n)",
  "Description": "Missing data imputation based on the 'missForest'\nalgorithm (Stekhoven, Daniel J (2012)\n<doi:10.1093/bioinformatics/btr597>) with adaptations for\nprediction settings. The function missForest() is used to\nimpute a (training) dataset with missing values and to learn\nimputation models that can be later used for imputing new\nobservations. The function missForestPredict() is used to\nimpute one or multiple new observations (test set) using the\nmodels learned on the training data. For more details see Albu,\nE., Gao, S., Wynants, L., & Van Calster, B. (2024).\nmissForestPredict--Missing data imputation for prediction\nsettings <doi:10.48550/arXiv.2407.03379>.",
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  "License": "GPL (>= 2)",
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    "check_predictor_matrix",
    "create_predictor_matrix",
    "evaluate_imputation_error",
    "missForest",
    "missForestPredict",
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    {
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      "title": "Calculates convergence based on NMSE",
      "topics": [
        "calculate_convergence"
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      "title": "Performs checks on a custom predictor matrix",
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        "check_predictor_matrix"
      ]
    },
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        "create_predictor_matrix"
      ]
    },
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      "title": "Evaluate the imputation error when true values are known.",
      "topics": [
        "evaluate_imputation_error"
      ]
    },
    {
      "page": "missForest",
      "title": "Imputes a dataframe and returns imputation models to be used on new observations",
      "topics": [
        "missForest"
      ]
    },
    {
      "page": "missForestPredict",
      "title": "Imputes a new dataframe based on the missForest models",
      "topics": [
        "missForestPredict"
      ]
    },
    {
      "page": "produce_NA",
      "title": "Produces a dataframe with missing values",
      "topics": [
        "produce_NA"
      ]
    },
    {
      "page": "prop_usable_cases",
      "title": "Calculates variable-wise proportion of usable cases (missing and observed)",
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        "prop_usable_cases"
      ]
    }
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      "title": "missForestPredict convergence criteria and error monitoring",
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