KOLMOGOROV_SMIRNOV computes the two-sample Kolmogorov-Smirnov test for each pair columns. If data size does not match, the data can be filled up with not-a-number (NaN). Usage: [D,ks,pval,df] = kolmogorov_smirnov(x,y); [...] = kolmogorov_smirnov(X); [...] = kolmogorov_smirnov(..,'Tail',tail); Input: x,y input vectors for comparison X data matrix, each column represents a sample distribution in case, the number of samples do not match, the matrix can can be filled up with not-a-number (NaN) values. tail: 'unequal' (default), 'larger', 'smaller' Output: D maximum absolute difference between sample data D(k,l) is the m.a.d. from X(:,k) and X(:,l) df is the degree-of freedom df(k,l) = n(k)*n(l)/(n(k)+n(l)) with n samples of corresponding column X. pval p-value, it's also a matrix where pval(k,l) is the p-value from column k and l. NOTE: For M data sets (M-columns of X), there are M*(M-1)/2 tests, you might want to consider some correction for multiple comparision. see also: kstest2, statistic/kolmogorov_smirnov_test_2
Package: nan