Mercurial > octave
view scripts/statistics/discrete_cdf.m @ 31090:1779a64b2510
maint: Merge stable to default
author | Arun Giridhar <arungiridhar@gmail.com> |
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date | Fri, 10 Jun 2022 18:57:17 -0400 |
parents | 5d3faba0342e |
children | 597f3ee61a48 |
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######################################################################## ## ## Copyright (C) 2010-2022 The Octave Project Developers ## ## See the file COPYRIGHT.md in the top-level directory of this ## distribution or <https://octave.org/copyright/>. ## ## 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 ## <https://www.gnu.org/licenses/>. ## ######################################################################## ## -*- texinfo -*- ## @deftypefn {} {@var{cdf} =} 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 <Invalid call> discrete_cdf () %!error <Invalid call> discrete_cdf (1) %!error <Invalid call> discrete_cdf (1,2) %!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])