📄 chisquare_test_homogeneity.m
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## Copyright (C) 1995, 1996, 1997 Kurt Hornik## ## This program 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 2, or (at your option)## any later version.## ## This program 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 this file. If not, write to the Free Software Foundation,## 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.## usage: [pval, chisq, df] = chisquare_test_homogeneity (x, y, c)#### Given two samples x and y, perform a chisquare test for homogeneity## of the null hypothesis that x and y come from the same distribution,## based on the partition induced by the (strictly increasing) entries## of c.#### For large samples, the test statistic chisq approximately follows a## chisquare distribution with df = length(c) degrees pf freedom. pval## is the p-value (1 minus the CDF of this distribution at chisq) of the## test.#### If no output argument is given, the p-value is displayed.## Author: KH <Kurt.Hornik@ci.tuwien.ac.at>## Description: Chi-square test for homogeneityfunction [pval, chisq, df] = chisquare_test_homogeneity (x, y, c) if (nargin != 3) usage ("[pval, chisq, df] = chisquare_test_homogeneity (x, y, c)"); endif if (! (is_vector(x) && is_vector(y) && is_vector(c))) error ("chisquare_test_homogeneity: x, y and c must be vectors"); endif ## Now test c for strictly increasing entries df = length (c); if (any ( (c(2 : df) - c(1 : (df - 1))) <= 0)) error ("chisquare_test_homogeneity: c must be increasing"); endif c = [(reshape (c, 1, df)), Inf]; l_x = length (x); x = reshape (x, l_x, 1); n_x = sum (x * ones (1, df+1) < ones (l_x, 1) * c); l_y = length (y); y = reshape (y, l_y, 1); n_y = sum(y * ones (1, df+1) < ones (l_y, 1) * c); chisq = l_x * l_y * sum ((n_x/l_x - n_y/l_y).^2 ./ (n_x + n_y)); pval = 1 - chisquare_cdf (chisq, df); if (nargout == 0) printf(" pval: %g\n", pval); endifendfunction
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