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## Copyright (C) 1996-2015 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
## <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn {Function File} {[@var{pval}, @var{tsq}] =} hotelling_test_2 (@var{x}, @var{y})
## For two samples @var{x} from multivariate normal distributions with
## the same number of variables (columns), unknown means and unknown
## equal covariance matrices, test the null hypothesis @code{mean
## (@var{x}) == mean (@var{y})}.
##
## Hotelling's two-sample @math{T^2} is returned in @var{tsq}. Under the null,
## @tex
## $$
## {(n_x+n_y-p-1) T^2 \over p(n_x+n_y-2)}
## $$
## @end tex
## @ifnottex
##
## @example
## (n_x+n_y-p-1) T^2 / (p(n_x+n_y-2))
## @end example
##
## @end ifnottex
## @noindent
## has an F distribution with @math{p} and @math{n_x+n_y-p-1} degrees of
## freedom, where @math{n_x} and @math{n_y} are the sample sizes and
## @math{p} is the number of variables.
##
## 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
## Author: KH <Kurt.Hornik@wu-wien.ac.at>
## Description: Compare means of two multivariate normals
function [pval, Tsq] = hotelling_test_2 (x, y)
if (nargin != 2)
print_usage ();
endif
if (isvector (x))
n_x = length (x);
if (! isvector (y))
error ("hotelling_test_2: if X is a vector, Y must also be a vector");
else
n_y = length (y);
p = 1;
endif
elseif (ismatrix (x))
[n_x, p] = size (x);
[n_y, q] = size (y);
if (p != q)
error ("hotelling_test_2: X and Y must have the same number of columns");
endif
else
error ("hotelling_test_2: X and Y must be matrices (or vectors)");
endif
d = mean (x) - mean (y);
S = ((n_x - 1) * cov (x) + (n_y - 1) * cov (y)) / (n_x + n_y - 2);
Tsq = (n_x * n_y / (n_x + n_y)) * d * (S \ d');
pval = 1 - fcdf ((n_x + n_y - p - 1) * Tsq / (p * (n_x + n_y - 2)),
p, n_x + n_y - p - 1);
if (nargout == 0)
printf (" pval: %g\n", pval);
endif
endfunction
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