VIM (version 6.2.2)

rangerImpute: Random Forest Imputation

Description

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

Usage

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

Value

the imputed data set.

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.

See Also

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

Examples

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