/usr/share/octave/packages/optim-1.4.1/nonlin_residmin.m is in octave-optim 1.4.1-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 | ## Copyright (C) 2010-2014 Olaf Till <i7tiol@t-online.de>
##
## This program 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.
##
## This program 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
## this program; if not, see <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn {Function File} {[@var{p}, @var{resid}, @var{cvg}, @var{outp}] =} nonlin_residmin (@var{f}, @var{pin})
## @deftypefnx {Function File} {[@var{p}, @var{resid}, @var{cvg}, @var{outp}] =} nonlin_residmin (@var{f}, @var{pin}, @var{settings})
## Frontend for nonlinear minimization of residuals returned by a model
## function.
##
## The functions supplied by the user have a minimal
## interface; any additionally needed constants (e.g. observed values)
## can be supplied by wrapping the user functions into anonymous
## functions.
##
## The following description applies to usage with vector-based
## parameter handling. Differences in usage for structure-based
## parameter handling will be explained separately.
##
## @var{f}: function returning the array of residuals. It gets a column
## vector of real parameters as argument. In gradient determination,
## this function may be called with an informational second argument,
## whose content depends on the function for gradient determination.
##
## @var{pin}: real column vector of initial parameters.
##
## @var{settings}: structure whose fields stand for optional settings
## referred to below. The fields can be set by @code{optimset()}.
##
## The returned values are the column vector of final parameters
## @var{p}, the final array of residuals @var{resid}, an integer
## @var{cvg} indicating if and how optimization succeeded or failed, and
## a structure @var{outp} with additional information, curently with the
## fields: @code{niter}, the number of iterations and
## @code{user_interaction}, information on user stops (see settings).
## The backend may define additional fields. @var{cvg} is greater than
## zero for success and less than or equal to zero for failure; its
## possible values depend on the used backend and currently can be
## @code{0} (maximum number of iterations exceeded), @code{2} (parameter
## change less than specified precision in two consecutive iterations),
## or @code{3} (improvement in objective function -- e.g. sum of squares
## -- less than specified), or @code{-1} (algorithm aborted by a user
## function).
##
## @c The following block will be cut out in the package info file.
## @c BEGIN_CUT_TEXINFO
##
## For settings, type @code{optim_doc ("nonlin_residmin")}.
##
## For desription of structure-based parameter handling, type
## @code{optim_doc ("parameter structures")}.
##
## For description of individual backends (currently only one), type
## @code{optim_doc ("residual optimization")} and choose the backend in
## the menu.
##
## @c END_CUT_TEXINFO
##
## @seealso {nonlin_curvefit}
## @end deftypefn
## PKG_ADD: __all_opts__ ("nonlin_residmin");
function [p, resid, cvg, outp] = nonlin_residmin (varargin)
if (nargin == 1)
p = __nonlin_residmin__ (varargin{1});
return;
endif
if (nargin < 2 || nargin > 3)
print_usage ();
endif
if (nargin == 2)
varargin{3} = struct ();
endif
varargin{4} = struct ();
[p, resid, cvg, outp] = __nonlin_residmin__ (varargin{:});
endfunction
%!demo
%! ## Example for linear inequality constraints
%! ## (see also the same example in 'demo nonlin_curvefit')
%!
%! ## independents
%! indep = 1:5;
%! ## residual function:
%! f = @ (p) p(1) * exp (p(2) * indep) - [1, 2, 4, 7, 14];
%! ## initial values:
%! init = [.25; .25];
%! ## linear constraints, A.' * parametervector + B >= 0
%! A = [1; -1]; B = 0; # p(1) >= p(2);
%! settings = optimset ("inequc", {A, B});
%!
%! ## start optimization
%! [p, residuals, cvg, outp] = nonlin_residmin (f, init, settings)
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