Mercurial > octave-nkf
view scripts/statistics/distributions/discrete_cdf.m @ 14138:72c96de7a403 stable
maint: update copyright notices for 2012
author | John W. Eaton <jwe@octave.org> |
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date | Mon, 02 Jan 2012 14:25:41 -0500 |
parents | 19b9f17d22af |
children | f3d52523cde1 |
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## Copyright (C) 2012 Rik Wehbring ## Copyright (C) 2010-2012 David Bateman ## ## 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} {} discrete_cdf (@var{x}, @var{v}, @var{p}) ## For each element of @var{x}, compute the cumulative distribution ## function (CDF) at @var{x} of a univariate discrete distribution which ## assumes the values in @var{v} with probabilities @var{p}. ## @end deftypefn function cdf = discrete_cdf (x, v, p) if (nargin != 3) print_usage (); endif if (! isvector (v)) error ("discrete_cdf: V must be a vector"); elseif (any (isnan (v))) error ("discrete_cdf: V must not have any NaN elements"); elseif (! isvector (p) || (length (p) != length (v))) error ("discrete_cdf: P must be a vector with length (V) elements"); elseif (! (all (p >= 0) && any (p))) error ("discrete_cdf: P must be a nonzero, non-negative vector"); endif p = p(:) / sum (p); # Reshape and normalize probability vector if (isa (x, "single") || isa (v, "single") || isa (p, "single")); cdf = NaN (size (x), "single"); else cdf = NaN (size (x)); endif k = !isnan (x); [vs, vi] = sort (v); cdf(k) = [0 ; cumsum(p(vi))](lookup (vs, x(k)) + 1); endfunction %!shared x,v,p,y %! x = [-1 0.1 1.1 1.9 3]; %! v = 0.1:0.2:1.9; %! p = 1/length(v) * ones(1, length(v)); %! y = [0 0.1 0.6 1 1]; %!assert(discrete_cdf ([x, NaN], v, p), [y, NaN], eps); %% Test class of input preserved %!assert(discrete_cdf (single([x, NaN]), v, p), single([y, NaN]), 2*eps("single")); %!assert(discrete_cdf ([x, NaN], single(v), p), single([y, NaN]), 2*eps("single")); %!assert(discrete_cdf ([x, NaN], v, single(p)), single([y, NaN]), 2*eps("single")); %% Test input validation %!error discrete_cdf () %!error discrete_cdf (1) %!error discrete_cdf (1,2) %!error discrete_cdf (1,2,3,4) %!error discrete_cdf (1, ones(2), ones(2,1)) %!error discrete_cdf (1, [1 ; NaN], ones(2,1)) %!error discrete_cdf (1, ones(2,1), ones(1,1)) %!error discrete_cdf (1, ones(2,1), [1 -1]) %!error discrete_cdf (1, ones(2,1), [1 NaN]) %!error discrete_cdf (1, ones(2,1), [0 0])