rangerImpute function

Random Forest Imputation

Impute missing values based on a random forest model using ranger::ranger()

rangerImpute(
  formula,
  data,
  imp_var = TRUE,
  imp_suffix = "imp",
  ...,
  verbose = FALSE,
  median = FALSE
)

Arguments

• formula: model formula for the imputation
• data: A data.frame containing the data
• imp_var: TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status
• imp_suffix: suffix used for TF imputation variables
• ...: Arguments passed to ranger::ranger()
• verbose: Show the number of observations used for training and evaluating the RF-Model. This parameter is also passed down to ranger::ranger() to show computation status.
• median: Use the median (rather than the arithmetic mean) to average the values of individual trees for a more robust estimate.

Returns

the imputed data set.

Examples

data(sleep)
rangerImpute(Dream+NonD~BodyWgt+BrainWgt,data=sleep)

See Also

Other imputation methods: hotdeck(), impPCA(), irmi(), kNN(), matchImpute(), medianSamp(), regressionImp(), sampleCat()