Overimpute main function — overimp • vismi

Overimp main function to call different imputation methods.

Usage

overimp(
  data,
  m = 5,
  p = 0.2,
  test_ratio = 0,
  method = "mixgb",
  seed = NULL,
  ...
)

data: A data frame with missing values.
m: The number of imputation.
p: The extra proportion of missing values.
test_ratio: The proportion of test set. Default is 0, meaning no test set.
method: The imputation method to use. One of "mixgb" (default), "mice" (mice with default per-variable methods), "mice-cart" (mice with classification and regression trees), or "mice-ranger" (mice with random forests via the ranger engine).
seed: Random seed.
...: Other arguments to be passed into the overimp function.

An overimp object containing imputed training, test data (if applicable) and essential parameters required for plotting.

if (requireNamespace("mixgb", quietly = TRUE)) {
  obj <- overimp(data = nhanes3, m = 3, p = 0.2, test_ratio = 0.2, method = "mixgb")
}