% test for correct size for iter = 1:10 vectorLength = randi([1 100]); result = fcn(vectorLength); assert(isequal([vectorLength, 1], size(result))); end

% get large sample vectorLength = 10000; result = fcn(vectorLength); % build empirical cumulative distribution function xEmpirical = sort(result); % x-axis yEmpirical = (1:vectorLength).' ./ vectorLength; % y-axis % build theoretical cumulative distribution function xTheoretical = xEmpirical; % x-axis erfInput = sqrt(0.5) / pi * (xTheoretical - exp(1)); yTheoretical = 0.5*erf(erfInput) + 0.5; % y-axis % compute statistics on diff between empirical and theoretical errorList = abs(yEmpirical - yTheoretical); errorMax = max(errorList); errorSum = sum(errorList); errorStd = std(errorList); % if fcn is correct, this should pass at least 99.9% of the time assert(errorMax < .02); assert(errorSum > 10.1); assert(errorStd > .00075);