Hi Is there a way to simulate correlated RVs where each RV follows poisson distribution? I have 2 RVs X1 and X2, and both follow Poisson distribution. I would like simulate final results such that I can control correlation between X1 and X2. Either simulating straight correlated process or post-processing of 2 independent run would work.
One way is to apply Knuth's Poisson generation using two correlated uniform distribution.
n = 10000; % correlation coef of uniform distribution % NOT of the poisson, but they are monotonically related Xcorr = 0.6; M12 = 2 * sin(pi * Xcorr / 6); M = [1, M12; M12, 1]; C = chol(M); % expectation value(s) lambda = 4; % scalar or vector of 1x2 Y = zeros(n,2); L = exp(-lambda); C = C / sqrt(2); for r=1:n k = zeros(1,2); p = ones(1,2); b = p > L; while any(p > L) k = k+double(b); X = (erf(randn(1,2)*C) + 1) / 2; p = p .* X; b = p > L; end Y(r,:) = k-1; end hist(Y,[0:12]) corrcoef(Y) mean(Y)
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