Weighted sampling without replacement

Question

I have a population p of indices and corresponding weights in vector w. I want to get k samples from this population without repla

Answer 1

An alternative to the for loop approach of petrichor that performs well if the number of samples is much smaller than the number of elements is to compute a weighted random sample with replacement and then remove duplicates. Of course, this is a very bad idea if the number of samples k is near the number of elements n, as this will require many iterations, but by avoiding for loops, the wall clock performance is often better. Your mileage may vary.

function I=randsample_noreplace(n,k,w)
I = sort(randsample(n, k, true, w));
while 1
    Idup = find( I(2:end)-I(1:end-1) ==0);
    if length(Idup) == 0
            break
    else
            I(Idup)=randsample(n, length(Idup), true, w);
            I = sort(I);
    end
end