Mercurial > hg > octave-thorsten
view scripts/statistics/base/kendall.m @ 5307:4c8a2e4e0717
[project @ 2005-04-26 19:24:27 by jwe]
author | jwe |
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date | Tue, 26 Apr 2005 19:24:47 +0000 |
parents | 38c61cbf086c |
children | 2a16423e4aa0 |
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## Copyright (C) 1995, 1996, 1997 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 2, 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, write to the Free ## Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA ## 02110-1301, USA. ## -*- texinfo -*- ## @deftypefn {Function File} {} kendall (@var{x}, @var{y}) ## Compute Kendall's @var{tau} for each of the variables specified by ## the input arguments. ## ## For matrices, each row is an observation and each column a variable; ## vectors are always observations and may be row or column vectors. ## ## @code{kendall (@var{x})} is equivalent to @code{kendall (@var{x}, ## @var{x})}. ## ## For two data vectors @var{x}, @var{y} of common length @var{n}, ## Kendall's @var{tau} is the correlation of the signs of all rank ## differences of @var{x} and @var{y}; i.e., if both @var{x} and ## @var{y} have distinct entries, then ## ## @iftex ## @tex ## $$ \tau = {1 \over n(n-1)} \sum_{i,j} {\rm sign}(q_i-q_j) {\rm sign}(r_i-r_j) $$ ## @end tex ## @end iftex ## @ifinfo ## @example ## 1 ## tau = ------- SUM sign (q(i) - q(j)) * sign (r(i) - r(j)) ## n (n-1) i,j ## @end example ## @end ifinfo ## ## @noindent ## in which the ## @iftex ## @tex ## $q_i$ and $r_i$ ## @end tex ## @end iftex ## @ifinfo ## @var{q}(@var{i}) and @var{r}(@var{i}) ## @end ifinfo ## are the ranks of ## @var{x} and @var{y}, respectively. ## ## If @var{x} and @var{y} are drawn from independent distributions, ## Kendall's @var{tau} is asymptotically normal with mean 0 and variance ## @code{(2 * (2@var{n}+5)) / (9 * @var{n} * (@var{n}-1))}. ## @end deftypefn ## Author: KH <Kurt.Hornik@ci.tuwien.ac.at> ## Description: Kendall's rank correlation tau function tau = kendall (x, y) if ((nargin < 1) || (nargin > 2)) usage ("kendall (x, y)"); endif if (rows (x) == 1) x = x'; endif [n, c] = size (x); if (nargin == 2) if (rows (y) == 1) y = y'; endif if (rows (y) != n) error ("kendall: x and y must have the same number of observations"); else x = [x, y]; endif endif r = ranks (x); m = sign (kron (r, ones (n, 1)) - kron (ones (n, 1), r)); tau = cor (m); if (nargin == 2) tau = tau (1 : c, (c + 1) : columns (x)); endif endfunction