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21## @deftypefn {Function File} {[@var{pval}, @var{z}] =} u_test (@var{x}, @var{y}, @var{alt})
22## For two samples @var{x} and @var{y}, perform a Mann-Whitney U-test of
23## the null hypothesis PROB (@var{x} > @var{y}) == 1/2 == PROB (@var{x}
24## < @var{y}). Under the null, the test statistic @var{z} approximately
25## follows a standard normal distribution. Note that this test is
26## equivalent to the Wilcoxon rank-sum test.
28## With the optional argument string @var{alt}, the alternative of
29## interest can be selected. If @var{alt} is @code{"!="} or
30## @code{"<>"}, the null is tested against the two-sided alternative
31## PROB (@var{x} > @var{y}) != 1/2. If @var{alt} is @code{">"}, the
32## one-sided alternative PROB (@var{x} > @var{y}) > 1/2 is considered.
33## Similarly for @code{"<"}, the one-sided alternative PROB (@var{x} >
34## @var{y}) < 1/2 is considered. The default is the two-sided case.
36## The p-value of the test is returned in @var{pval}.
38## If no output argument is given, the p-value of the test is displayed.
41## This implementation is still incomplete---for small sample sizes,
42## the normal approximation is rather bad ...
44## Author: KH <Kurt.Hornik@wu-wien.ac.at>
45## Description: Mann-Whitney U-test
47function [pval, z] = u_test (x, y, alt)
49 if ((nargin < 2) || (nargin > 3))
53 if (! (isvector (x) && isvector (y)))
54 error ("u_test: both x and y must be vectors");
59 r = ranks ([(reshape (x, 1, n_x)), (reshape (y, 1, n_y))]);
60 z = (sum (r(1 : n_x)) - n_x * (n_x + n_y + 1) / 2) ...
61 / sqrt (n_x * n_y * (n_x + n_y + 1) / 12);
63 cdf = stdnormal_cdf (z);
70 error("u_test: alt must be a string");
72 if (strcmp (alt, "!=") || strcmp (alt, "<>"))
73 pval = 2 * min (cdf, 1 - cdf);
74 elseif (strcmp (alt, ">"))
76 elseif (strcmp (alt, "<"))
79 error ("u_test: option %s not recognized", alt);
83 printf (" pval: %g\n", pval);