The goal of missMethods is to make the creation and handling of missing data as well as the evaluation of missing data methods easier.
You can install the released version of missMethods from CRAN with:
install.packages("missMethods")
And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("torockel/missMethods")
missMethods mainly provides three types of functions:
delete_
functions for generating missing valuesimpute_
functions for imputing missing valuesevaluate_
functions for evaluating missing data methodsRun help(package = "missMethods")
to see all functions. More details
for the delete_
functions are given in a vignette (run
vignette("Generating-missing-values")
).
This is a very basic workflow to generate missing values, impute the generated missing values and evaluate the imputation result:
library(missMethods)
set.seed(123)
ds_comp <- data.frame(X = rnorm(100), Y = rnorm(100))
ds_mis <- delete_MCAR(ds_comp, 0.3)
ds_imp <- impute_mean(ds_mis)
evaluate_imputed_values(ds_imp, ds_comp, "RMSE")
#> [1] 0.5328238
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