Dear R-users,
i try to generate missing values in a matrix X according to a given
missingnes pattern R with the probabilities p per row.
X<-matrix(rnorm(3*100),ncol=3)
## indicator matrix for missingnes (1 observed, 0 missing)
R<-matrix(c(1,1,1,
0,0,1,
1,1,0,
0,1,1),ncol=3,byrow=TRUE)
## probabilities for row 1, row 2, row 3 and row 4
p<-c(0.375,0.25,0.25,0.125)
## does not exactly what i want, because i get rows
## of missinges pattern which are not in R
X[rbinom(100,1,p[1])==1,R[1,]==1] <- NA
X[rbinom(100,1,p[2])==1,R[2,]==1] <- NA
X[rbinom(100,1,p[3])==1,R[3,]==1] <- NA
X[rbinom(100,1,p[4])==1,R[4,]==1] <- NA
So it would be great if i can get any advice how to do this. I also
tried rmultinom or sample but without any success so far.
Another question is what to to if want the missing pattern R and
simulate a certain amount of missingnes mybe about 10 %? I guess i have
to mix the probabilities for each row in such a way to get approximatly
the wanted missingnes in percent.
best regards
Andreas
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