imputeR (version 2.2)

SimIm: Introduce some missing values into a data matrix

Description

This function randomly introduce some amount of missing values into a matrix.

Usage

SimIm(data, p = 0.1)

Arguments

data

a data matrix to simulate

p

the percentage of missing values introduced into the data matrix it should be a value between 0 and 1.

Value

the same size matrix with simulated missing values.

Examples

# NOT RUN {
# Create data without missing values as example
simdata <- matrix(rnorm(100), 10, 10)

# Now let's introduce some missing values into the dataset
missingdata <- SimIm(simdata, p = 0.15)

# count the number of missing values afterwards
sum(is.na(missingdata))

#------------------

# There is no missing values in the original parkinson data
data(parkinson)

# Let's introduce some missing values into the dataset
missdata <- SimIm(parkinson, 0.1)

# count the number of missing values afterwards
sum(is.na(missdata))
# }