I am trying to generate a binary matrix where every row in the matrix is
guaranteed to have at least one 1. Ideally, I would like most rowSums to be
equal to 2 or 3 with some 1s and some 4s. But, rowSums cannot be equal to 0.
I can tinker with the vector of probability weights, but in doing so (in the
way I am doing it) this causes for more rowSums to be equal to 4 than I ideally
would like, but this never helps to guarantee a rowSum will not be equal to 0.
I could post-hoc tinker with any rows that are all 0, but seems like that may
be just inefficient.
Below is sample code, any ideas on how to best tackle this?
Harold
dimMat <- matrix(0, 1000, 4)
for(i in 1:1000){
dimMat[i, ] <- sample(c(0,1), 4, replace = TRUE, prob = c(.3,
.7))
}
table(rowSums(dimMat))
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