Mercurial > octave-nkf
view scripts/statistics/base/std.m @ 20266:83792dd9bcc1
Use in-place operators in m-files where possible.
* scripts/audio/@audioplayer/set.m, scripts/audio/@audiorecorder/set.m,
scripts/audio/mu2lin.m, scripts/elfun/cosd.m, scripts/general/del2.m,
scripts/general/profexplore.m, scripts/general/quadl.m, scripts/general/rat.m,
scripts/general/rotdim.m, scripts/help/get_first_help_sentence.m,
scripts/help/private/__strip_html_tags__.m, scripts/image/cubehelix.m,
scripts/io/textread.m, scripts/linear-algebra/duplication_matrix.m,
scripts/linear-algebra/housh.m, scripts/linear-algebra/krylov.m,
scripts/linear-algebra/logm.m, scripts/linear-algebra/normest.m,
scripts/linear-algebra/onenormest.m, scripts/optimization/fminsearch.m,
scripts/optimization/lsqnonneg.m, scripts/optimization/qp.m,
scripts/plot/appearance/annotation.m, scripts/plot/appearance/axis.m,
scripts/plot/appearance/legend.m, scripts/plot/appearance/specular.m,
scripts/plot/draw/colorbar.m, scripts/plot/draw/hist.m,
scripts/plot/draw/plotmatrix.m, scripts/plot/draw/private/__stem__.m,
scripts/plot/util/__actual_axis_position__.m,
scripts/plot/util/__gnuplot_drawnow__.m, scripts/plot/util/findobj.m,
scripts/plot/util/print.m, scripts/plot/util/private/__go_draw_axes__.m,
scripts/plot/util/private/__print_parse_opts__.m, scripts/plot/util/rotate.m,
scripts/polynomial/pchip.m, scripts/polynomial/polyaffine.m,
scripts/polynomial/polyder.m, scripts/polynomial/private/__splinefit__.m,
scripts/polynomial/residue.m, scripts/signal/arch_fit.m,
scripts/signal/arch_rnd.m, scripts/signal/bartlett.m,
scripts/signal/blackman.m, scripts/signal/freqz.m, scripts/signal/hamming.m,
scripts/signal/hanning.m, scripts/signal/spectral_adf.m,
scripts/signal/spectral_xdf.m, scripts/signal/stft.m,
scripts/sparse/bicgstab.m, scripts/sparse/cgs.m,
scripts/sparse/private/__sprand_impl__.m, scripts/sparse/qmr.m,
scripts/sparse/sprandsym.m, scripts/sparse/svds.m, scripts/specfun/legendre.m,
scripts/special-matrix/gallery.m, scripts/statistics/base/gls.m,
scripts/statistics/models/logistic_regression.m,
scripts/statistics/tests/kruskal_wallis_test.m,
scripts/statistics/tests/manova.m, scripts/statistics/tests/wilcoxon_test.m,
scripts/time/datevec.m:
Use in-place operators in m-files where possible.
author | Rik <rik@octave.org> |
---|---|
date | Tue, 26 May 2015 21:07:42 -0700 |
parents | d9341b422488 |
children |
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## Copyright (C) 1996-2015 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}) ## Compute the standard deviation of the elements of the vector @var{x}. ## ## The standard deviation is defined as ## @tex ## $$ ## {\rm std} (x) = \sigma = \sqrt{{\sum_{i=1}^N (x_i - \bar{x})^2 \over N - 1}} ## $$ ## where $\bar{x}$ is the mean value of $x$ and $N$ is the number of elements. ## @end tex ## @ifnottex ## ## @example ## @group ## std (x) = sqrt ( 1/(N-1) SUM_i (x(i) - mean(x))^2 ) ## @end group ## @end example ## ## @noindent ## where @math{N} is the number of elements. ## @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: ## normalize with @math{N-1}, provides the square root of the best unbiased ## estimator of the variance [default] ## ## @item 1: ## normalize with @math{N}, this provides the square root of the second ## moment around the mean ## @end table ## ## If the optional argument @var{dim} is given, operate along this dimension. ## @seealso{var, range, iqr, mean, median} ## @end deftypefn ## Author: jwe function retval = std (x, opt = 0, dim) if (nargin < 1 || nargin > 3) print_usage (); endif if (! (isnumeric (x) || islogical (x))) error ("std: X must be a numeric vector or matrix"); endif if (isempty (opt)) opt = 0; endif if (opt != 0 && opt != 1) error ("std: normalization OPT must be 0 or 1"); endif nd = ndims (x); sz = size (x); if (nargin < 3) ## Find the first non-singleton dimension. (dim = find (sz > 1, 1)) || (dim = 1); else if (!(isscalar (dim) && dim == fix (dim)) || !(1 <= dim && dim <= nd)) error ("std: DIM must be an integer and a valid dimension"); endif endif n = sz(dim); if (n == 1 || isempty (x)) if (isa (x, "single")) retval = zeros (sz, "single"); else retval = zeros (sz); endif else retval = sqrt (sumsq (center (x, dim), dim) / (n - 1 + opt)); endif endfunction %!test %! x = ones (10, 2); %! y = [1, 3]; %! assert (std (x), [0, 0]); %! assert (std (y), sqrt (2), sqrt (eps)); %! assert (std (x, 0, 2), zeros (10, 1)); %!assert (std (ones (3, 1, 2), 0, 2), zeros (3, 1, 2)); %!assert (std ([1 2], 0), sqrt (2)/2, 5*eps); %!assert (std ([1 2], 1), 0.5, 5*eps); %!assert (std (1), 0); %!assert (std (single (1)), single (0)); %!assert (std ([]), []); %!assert (std (ones (1,3,0,2)), ones (1,3,0,2)); ## Test input validation %!error std () %!error std (1, 2, 3, 4) %!error std (['A'; 'B']) %!error std (1, -1)