Mercurial > octave
view scripts/signal/arma_rnd.m @ 31248:8b75954a4670
delaunayn: adjust node ordering for positive outward normal vectors (bug #53397)
* delaunayn.m: Check sign of simplex volume, flip node order for negative
volumes to ensure positive (outward-pointing) normal vectors. Add BISTs to
check for positive volumes.
* etc/News.8.md: Append function improvement note to delaunayn change
paragraph under General Improvements.
author | Nicholas R. Jankowski <jankowski.nicholas@gmail.com> |
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date | Thu, 29 Sep 2022 23:09:05 -0400 |
parents | 5d3faba0342e |
children | 597f3ee61a48 |
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######################################################################## ## ## Copyright (C) 1995-2022 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{x} =} arma_rnd (@var{a}, @var{b}, @var{v}, @var{t}, @var{n}) ## Return a simulation of the ARMA model. ## ## The ARMA model is defined by ## ## @example ## @group ## x(n) = a(1) * x(n-1) + @dots{} + a(k) * x(n-k) ## + e(n) + b(1) * e(n-1) + @dots{} + b(l) * e(n-l) ## @end group ## @end example ## ## @noindent ## in which @var{k} is the length of vector @var{a}, @var{l} is the length of ## vector @var{b} and @var{e} is Gaussian white noise with variance @var{v}. ## The function returns a vector of length @var{t}. ## ## The optional parameter @var{n} gives the number of dummy @var{x}(@var{i}) ## used for initialization, i.e., a sequence of length @var{t}+@var{n} is ## generated and @var{x}(@var{n}+1:@var{t}+@var{n}) is returned. If @var{n} ## is omitted, @var{n} = 100 is used. ## @end deftypefn function x = arma_rnd (a, b, v, t, n = 100) if (nargin < 4) print_usage (); endif if ((min (size (a)) > 1) || (min (size (b)) > 1)) error ("arma_rnd: A and B must not be matrices"); endif if (! isscalar (t)) error ("arma_rnd: T must be a scalar"); endif if (! isscalar (n)) error ("arma_rnd: N must be a scalar"); endif ar = length (a); br = length (b); a = reshape (a, ar, 1); b = reshape (b, br, 1); ## Apply our notational convention. a = [1; -a]; b = [1; b]; n = min (n, ar + br); e = sqrt (v) * randn (t + n, 1); x = filter (b, a, e); x = x(n + 1 : t + n); endfunction