Doran, Harold <HDoran <at> air.org> writes:
> I am trying to generate a binary matrix where
row
in the matrix is guaranteed to have at
least one 1.
> Ideally, I would like most rowSums to be equal
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
so (in the way I am doing it) this
causes for
> more rowSums to be equal to 4 than I ideally would
, but this never helps to guarantee a
rowSum will not be
> equal to 0. I could post-hoc tinker with any rows
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))
Wht don't you sample from the distribution of row sums
for each row and then distribute that many 1's randomly
among the columns.
Ken
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