called for its side effect. The return value is not defined.
Details
The different types of missings are drawn in quasi-self-understandable
colors: normal gray for NMV, and lightgray as for BDT (since they contain
semi-numeric information), yellow (slight warning) for MAR, red (serious
warning) for MNAR, white (because they are non-existing) for SZ, and
magenta for the strange case of errors.
# NOT RUN {data(SimulatedAmounts)
x <- acomp(sa.lognormals)
xnew <- simulateMissings(x,dl=0.05,MAR=0.05,MNAR=0.05,SZ=0.05)
xnew
plot(missingSummary(xnew))
# }