--- a/scripts/statistics/tests/u_test.m	Tue Jan 18 08:32:15 2000 +0000
+++ b/scripts/statistics/tests/u_test.m	Tue Jan 18 10:13:39 2000 +0000
@@ -14,25 +14,25 @@
 ## along with this file.  If not, write to the Free Software Foundation,
 ## 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
 
-## usage:  [pval, z] = u_test (x, y [, alt])
-##
-## For two samples x and y, perform a Mann-Whitney U-test of the null
-## hypothesis PROB(x > y) == 1/2 == PROB(x < y).  Under the null, the
-## test statistic z approximately follows a standard normal
-## distribution.  Note that this test is equivalent to the Wilcoxon
-## rank-sum test.
+## -*- texinfo -*-
+## @deftypefn {Function File} {[@var{pval}, @var{z}] =} u_test (@var{x}, @var{y}, @var{alt})
+## For two samples @var{x} and @var{y}, perform a Mann-Whitney U-test of
+## the null hypothesis PROB (@var{x} > @var{y}) == 1/2 == PROB (@var{x}
+## < @var{y}).  Under the null, the test statistic @var{z} approximately
+## follows a standard normal distribution.  Note that this test is
+## equivalent to the Wilcoxon rank-sum test.
 ##
-## With the optional argument string alt, the alternative of interest
-## can be selected.
-## If alt is "!=" or "<>", the null is tested against the two-sided
-## alternative PROB(x > y) != 1/2.
-## If alt is ">", the one-sided alternative PROB(x > y) > 1/2 is
-## considered, similarly for "<".
-## The default is the two-sided case.
+## With the optional argument string @var{alt}, the alternative of
+## interest can be selected.  If @var{alt} is @code{"!="} or
+## @code{"<>"}, the null is tested against the two-sided alternative
+## PROB (@var{x} > @var{y}) != 1/2.  If @var{alt} is @code{">"}, the
+## one-sided alternative PROB (@var{x} > @var{y}) > 1/2 is considered,
+## similarly for @code{"<"}.  The default is the two-sided case.
 ##
-## pval is the p-value of the test.
+## The p-value of the test is returned in @var{pval}.
 ##
 ## If no output argument is given, the p-value of the test is displayed.
+## @end deftypefn
 
 ## This implementation is still incomplete---for small sample sizes,
 ## the normal approximation is rather bad ...