Mercurial > hg > octave-lyh
view scripts/statistics/base/std.m @ 5053:c08cb1098afc
[project @ 2004-10-19 23:10:54 by jwe]
author | jwe |
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date | Tue, 19 Oct 2004 23:10:55 +0000 |
parents | 9f7ef92b50b0 |
children | 4c8a2e4e0717 |
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## Copyright (C) 1996, 1997 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 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, 59 Temple Place - Suite 330, Boston, MA ## 02111-1307, USA. ## -*- 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 ## $$ ## {\rm std} (x) = \sigma (x) = \sqrt{{\sum_{i=1}^N (x_i - \bar{x}) \over N - 1}} ## $$ ## @end tex ## @end iftex ## @ifinfo ## ## @example ## @group ## std (x) = sqrt (sumsq (x - mean (x)) / (n - 1)) ## @end group ## @end example ## @end ifinfo ## 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 N-1, provides the square root of best unbiased estimator of ## the variance [default] ## @item 1: ## normalizes with 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. ## @end deftypefn ## ## @seealso{mean and median} ## Author: jwe function retval = std (a, opt, dim) if (nargin < 1 || nargin > 3) usage ("std (a, opt, dim)"); endif if nargin < 3 dim = min(find(size(a)>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