simulate_missings {NADIA} | R Documentation |
Generate MCAR missings in dataset.
Description
Function generates random missing values in given dataset according to set parameters.
Usage
simulate_missings(
df,
per_missings,
per_instances_missings = NULL,
per_variables_missings = NULL,
variables_with_missings = NULL
)
Arguments
df |
Data.frame or data.table where missing values will be generated |
per_missings |
Overall percentage of missing values generated in dataset. Must be set every time. |
per_instances_missings |
Percentage of instances which will have missing values. |
per_variables_missings |
Percentage of variables which will have missing values. |
variables_with_missings |
Only when 'per_variables_missings' is 'NULL'. Vector of column indexes where missings will be generated. |
Value
Dataset with generated missings.
Examples
{
data_NA <- simulate_missings(iris, 20)
# check
sum(is.na(data_NA)) > 0
}
[Package NADIA version 0.4.2 Index]