Mercurial > hg > octave-lyh
view scripts/statistics/base/cov.m @ 7411:83a8781b529d
[project @ 2008-01-22 21:52:25 by jwe]
author | jwe |
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date | Tue, 22 Jan 2008 21:52:26 +0000 |
parents | a1dbe9d80eee |
children | 18d7171759ff |
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## Copyright (C) 1995, 1996, 1997, 1998, 1999, 2000, 2002, 2004, 2005, ## 2006, 2007 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} {} cov (@var{x}, @var{y}) ## Compute covariance. ## ## If each row of @var{x} and @var{y} is an observation and each column is ## a variable, the (@var{i}, @var{j})-th entry of ## @code{cov (@var{x}, @var{y})} is the covariance between the @var{i}-th ## variable in @var{x} and the @var{j}-th variable in @var{y}. ## @iftex ## @tex ## $$ ## \sigma_{ij} = {1 \over N-1} \sum_{i=1}^N (x_i - \bar{x})(y_i - \bar{y}) ## $$ ## where $\bar{x}$ and $\bar{y}$ are the mean values of $x$ and $y$. ## @end tex ## @end iftex ## If called with one argument, compute @code{cov (@var{x}, @var{x})}. ## @end deftypefn ## Author: KH <Kurt.Hornik@wu-wien.ac.at> ## Description: Compute covariances function c = cov (x, y) if (nargin < 1 || nargin > 2) print_usage (); endif if (rows (x) == 1) x = x'; endif n = rows (x); if (nargin == 2) if (rows (y) == 1) y = y'; endif if (rows (y) != n) error ("cov: x and y must have the same number of observations"); endif x = x - ones (n, 1) * sum (x) / n; y = y - ones (n, 1) * sum (y) / n; c = conj (x' * y / (n - 1)); elseif (nargin == 1) x = x - ones (n, 1) * sum (x) / n; c = conj (x' * x / (n - 1)); endif endfunction %!test %! x = rand (10); %! cx1 = cov (x); %! cx2 = cov (x, x); %! assert(size (cx1) == [10, 10] && size (cx2) == [10, 10] && cx1 == cx2); %!error cov (); %!error cov (1, 2, 3);