impute_missing_values: Impute Missing Values

In mackerman44/DASH: DASH: Drone Assisted Stream Habitat

Impute Missing Values

Description

Impute any missing values from selected columns within a data.frame

Usage

impute_missing_values(
  data_df = NULL,
  col_nm_vec = NULL,
  method = c("randomForestSRC", "missForest", "Hmisc"),
  my_seed = 5,
  ntree = 1000,
  nk = 4,
  ...
)

Arguments

data_df	data.frame with potential missing values
col_nm_vec	character vector of column names that should be either imputed and/or used to impute other columns
method	which method to use, either by creating random forests using the missForest package, or by predictive mean matching using the aregImpute() function in the Hmisc package
my_seed	seed for random number generator, to make results reproducible
ntree	how many trees to build if missForest or randomForestSRC
nk	how many knots to use in smoothing splines if using method = 'Hmisc'
...	other arguments to be passed to either missForest::missForest(), Hmisc::aregImpute(), or randomForestSRC::impute() functions

Value

a data.frame with the same dimensions as the original, but with no missing values

Author(s)

Kevin see

mackerman44/DASH documentation built on Sept. 5, 2024, 8:14 a.m.