X-Git-Url: https://git.creatis.insa-lyon.fr/pubgit/?a=blobdiff_plain;f=octave_packages%2Fm%2Fstatistics%2Ftests%2Fkruskal_wallis_test.m;fp=octave_packages%2Fm%2Fstatistics%2Ftests%2Fkruskal_wallis_test.m;h=50410ba8216cc2c7496c9f27ffd1c6d4ebdbbf2b;hb=1c0469ada9531828709108a4882a751d2816994a;hp=0000000000000000000000000000000000000000;hpb=63de9f36673d49121015e3695f2c336ea92bc278;p=CreaPhase.git diff --git a/octave_packages/m/statistics/tests/kruskal_wallis_test.m b/octave_packages/m/statistics/tests/kruskal_wallis_test.m new file mode 100644 index 0000000..50410ba --- /dev/null +++ b/octave_packages/m/statistics/tests/kruskal_wallis_test.m @@ -0,0 +1,98 @@ +## Copyright (C) 1995-2012 Kurt Hornik +## +## This file is part of Octave. +## +## Octave is free software; you can redistribute it and/or modify it +## under the terms of the GNU General Public License as published by +## the Free Software Foundation; either version 3 of the License, or (at +## your option) any later version. +## +## Octave is distributed in the hope that it will be useful, but +## WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +## General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with Octave; see the file COPYING. If not, see +## . + +## -*- texinfo -*- +## @deftypefn {Function File} {[@var{pval}, @var{k}, @var{df}] =} kruskal_wallis_test (@var{x1}, @dots{}) +## Perform a Kruskal-Wallis one-factor "analysis of variance". +## +## Suppose a variable is observed for @var{k} > 1 different groups, and +## let @var{x1}, @dots{}, @var{xk} be the corresponding data vectors. +## +## Under the null hypothesis that the ranks in the pooled sample are not +## affected by the group memberships, the test statistic @var{k} is +## approximately chi-square with @var{df} = @var{k} - 1 degrees of +## freedom. +## +## If the data contains ties (some value appears more than once) +## @var{k} is divided by +## +## 1 - @var{sum_ties} / (@var{n}^3 - @var{n}) +## +## where @var{sum_ties} is the sum of @var{t}^2 - @var{t} over each group +## of ties where @var{t} is the number of ties in the group and @var{n} +## is the total number of values in the input data. For more info on +## this adjustment see "Use of Ranks in One-Criterion Variance Analysis" +## in Journal of the American Statistical Association, Vol. 47, +## No. 260 (Dec 1952) by William H. Kruskal and W. Allen Wallis. +## +## The p-value (1 minus the CDF of this distribution at @var{k}) is +## returned in @var{pval}. +## +## If no output argument is given, the p-value is displayed. +## @end deftypefn + +## Author: KH +## Description: Kruskal-Wallis test + +function [pval, k, df] = kruskal_wallis_test (varargin) + + m = nargin; + if (m < 2) + print_usage (); + endif + + n = []; + p = []; + + for i = 1 : m; + x = varargin{i}; + if (! isvector (x)) + error ("kruskal_wallis_test: all arguments must be vectors"); + endif + l = length (x); + n = [n, l]; + p = [p, (reshape (x, 1, l))]; + endfor + + r = ranks (p); + + k = 0; + j = 0; + for i = 1 : m; + k = k + (sum (r ((j + 1) : (j + n(i))))) ^ 2 / n(i); + j = j + n(i); + endfor + + n = length (p); + k = 12 * k / (n * (n + 1)) - 3 * (n + 1); + + ## Adjust the result to takes ties into account. + sum_ties = sum (polyval ([1, 0, -1, 0], runlength (sort (p)))); + k = k / (1 - sum_ties / (n^3 - n)); + + df = m - 1; + pval = 1 - chi2cdf (k, df); + + if (nargout == 0) + printf ("pval: %g\n", pval); + endif + +endfunction + +## Test with ties +%!assert (abs(kruskal_wallis_test([86 86], [74]) - 0.157299207050285) < 0.0000000000001)