marginplot(x, delimiter = NULL, col = c("skyblue","red","red4","orange",
"orange4"), alpha = NULL, pch = c(1,16), cex = par("cex"),
numbers = TRUE, cex.numbers = par("cex"), zeros = FALSE, xlim = NULL,
ylim = NULL, main = NULL, sub = NULL, xlab = NULL, ylab = NULL,
ann = par("ann"), axes = TRUE, frame.plot = axes, ...)matrix or data.frame with two columns.x needs
to have colnames). If given, it is used to determine the correspondNULL. This can be used to prevent overplotting.TRUE, only the non-zero observations are used for drawing the
respective boxplot. If a singmain,
sub, xlab, ylab) should be displayed."xaxt" or "yaxt" to suppress
only one of the axes.par).Imputed values in either of the variables are highlighted in the scatterplot.
Furthermore, the frequencies of the missing/imputed values can be displayed by a number (lower left of the plot). The number in the lower left corner is the number of observations that are missing/imputed in both variables.
scattMissdata(tao, package = "VIM")
data(chorizonDL, package = "VIM")
## for missing values
marginplot(tao[,c("Air.Temp", "Humidity")])
marginplot(log10(chorizonDL[,c("CaO", "Bi")]))
## for imputed values
marginplot(kNN(tao[,c("Air.Temp", "Humidity")]), delimiter = "_imp")
marginplot(kNN(log10(chorizonDL[,c("CaO", "Bi")])), delimiter = "_imp")Run the code above in your browser using DataLab