Mercurial > hg > octave-lyh
view scripts/statistics/base/std.m @ 7017:a1dbe9d80eee
[project @ 2007-10-12 21:27:11 by jwe]
author | jwe |
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date | Fri, 12 Oct 2007 21:27:37 +0000 |
parents | 93c65f2a5668 |
children | 83a8781b529d |
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## Copyright (C) 1996, 1997, 1998, 1999, 2000, 2004, 2005, 2006, 2007 ## John W. Eaton ## ## 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} {} std (@var{x}) ## @deftypefnx {Function File} {} std (@var{x}, @var{opt}) ## @deftypefnx {Function File} {} std (@var{x}, @var{opt}, @var{dim}) ## If @var{x} is a vector, compute the standard deviation of the elements ## of @var{x}. ## @iftex ## @tex ## $$ ## {\rm std} (x) = \sigma (x) = \sqrt{{\sum_{i=1}^N (x_i - \bar{x})^2 \over N - 1}} ## $$ ## where $\bar{x}$ is the mean value of $x$. ## @end tex ## @end iftex ## @ifnottex ## ## @example ## @group ## std (x) = sqrt (sumsq (x - mean (x)) / (n - 1)) ## @end group ## @end example ## @end ifnottex ## If @var{x} is a matrix, compute the standard deviation for ## each column and return them in a row vector. ## ## The argument @var{opt} determines the type of normalization to use. Valid values ## are ## ## @table @asis ## @item 0: ## normalizes with @math{N-1}, provides the square root of best unbiased estimator of ## the variance [default] ## @item 1: ## normalizes with @math{N}, this provides the square root of the second moment around ## the mean ## @end table ## ## The third argument @var{dim} determines the dimension along which the standard ## deviation is calculated. ## @seealso{mean, median} ## @end deftypefn ## Author: jwe function retval = std (a, opt, dim) if (nargin < 1 || nargin > 3) print_usage (); endif if nargin < 3 dim = find (size (a) > 1, 1); if isempty(dim), dim=1; endif; endif if ((nargin < 2) || isempty(opt)) opt = 0; endif sz = size(a); if (sz (dim) == 1) retval = zeros(sz); elseif (numel (a) > 0) rng = ones (1, length (sz)); rng (dim) = sz (dim); if (opt == 0) retval = sqrt (sumsq (a - repmat(mean (a, dim), rng), dim) / (sz(dim) - 1)); else retval = sqrt (sumsq (a - repmat(mean (a, dim), rng), dim) / sz(dim)); endif else error ("std: invalid matrix argument"); endif endfunction