39 lines
966 B
Matlab
39 lines
966 B
Matlab
% generate correlated data:
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n=200;
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a=0.2;
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x = randn(n, 1);
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y = randn(n, 1) + a*x;
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% correlation coefficient:
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rd = corr(x, y);
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fprintf('correlation coefficient of data r = %.2f\n', rd);
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% distribution of null hypothesis by permutation:
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nperm = 1000;
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rs = zeros(nperm,1);
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for i=1:nperm
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xr=x(randperm(length(x))); % shuffle x
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yr=y(randperm(length(y))); % shuffle y
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rs(i) = corr(xr, yr);
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end
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[h,b] = hist(rs, 20);
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h = h/sum(h)/(b(2)-b(1)); % normalization
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% significance:
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rq = quantile(rs, 0.95);
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fprintf('correlation coefficient of null hypothesis at 5%% significance = %.2f\n', rq);
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if rd >= rq
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fprintf('--> correlation r=%.2f is significant\n', rd);
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else
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fprintf('--> r=%.2f is not a significant correlation\n', rd);
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end
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% plot:
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bar(b, h, 'facecolor', 'b');
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hold on;
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bar(b(b>=rq), h(b>=rq), 'facecolor', 'r');
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plot([rd rd], [0 4], 'r', 'linewidth', 2);
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xlabel('Correlation coefficient');
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ylabel('Probability density of H0');
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hold off;
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