Plot the dataset with marks where there are missing value. It allows to have a quick idea of the structure of missing values (Missing at Random or not for example).

showdata(X = X, what = c("miss", "correl"), pch = 7)

Arguments

X

the matrix to analyse (matrix with missing values or correlations matrix)

what

indicates what to plot. If what="correl" and X is a correlation matrix then the plot is a correlation plot. Else it shows the missing values positions in the dataset.

pch

for missing, symbol to plot (can set pch="." for large datasets)

Examples

data <- mtcars datamiss = Terminator(target = data, wrath = 0.05) # 5% of missing values showdata(datamiss) # plot positions of the missing values
# missing values with a structure datamiss = Terminator(target = data, diag = 1) # diag of missing values showdata(datamiss) # plot positions of the missing values (no full individuals, no full variable)
opar = par(no.readonly = TRUE) showdata(X = cor(data), what = "correl")
par(opar)