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diff --git a/octave_packages/optim-1.2.0/private/__covp_corp_wls__.m b/octave_packages/optim-1.2.0/private/__covp_corp_wls__.m
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+++ b/octave_packages/optim-1.2.0/private/__covp_corp_wls__.m
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+## Copyright (C) 2011 Olaf Till <olaf.till@uni-jena.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/>.
+
+## This is based on Bard, Nonlinear Parameter Estimation, Academic
+## Press, 1974, section 7-5, but also on own re-calculations for the
+## specific case of weighted least squares. The part with only certain
+## elements of covp or corp being defined is self-made, I don't know a
+## reference.
+
+function hook = __covp_corp_wls__ (hook)
+
+  ## compute jacobian, if not already done
+  if (! isfield (hook, "jac"))
+    hook.jac = hook.dfdp (hook.pfin, hook);
+  endif
+  jact = (jac = hook.jac).';
+
+  ## compute guessed covariance matrix of data, if not already done
+  if (! isfield (hook, "covd"))
+    hook = hook.funs.covd (hook);
+  endif
+  covd_inv = inv (covd = hook.covd);
+
+  if (rcond (A = jact * covd_inv * jac) > eps)
+
+    covp = hook.covp = inv (A);
+
+    d = sqrt (diag (covp));
+
+    hook.corp = covp ./ (d * d.');
+
+  else
+
+    n = hook.np;
+
+    covp = NA (n);
+
+    ## Now we have the equation "A * covp * A.' == A".
+
+    ## Find a particular solution for "covp * A.'".
+    part_covp_At = A \ A;
+
+    ## Find a particular solution for "covp". Only uniquely defined
+    ## elements (identified later) will be further used.
+    part_covp = A \ part_covp_At.';
+
+    ## Find a basis for the nullspace of A.
+    if (true) # test for Octave version once submitted patch is applied
+				# to Octave (bug #33503)
+      null = @ __null_optim__;
+    endif
+    if (isempty (basis = null (A)))
+      error ("internal error, singularity assumed, but null-space computed to be zero-dimensional");
+    endif
+
+    ## Find an index (applied to both row and column) of uniquely
+    ## defined elements of covp.
+    idun = all (basis == 0, 2);
+
+    ## Fill in these elements.
+    covp(idun, idun) = part_covp(idun, idun);
+
+    ## Compute corp as far as possible at the moment.
+    d = sqrt (diag (covp));
+    corp = covp ./ (d * d.');
+
+    ## All diagonal elements of corp should be one, even those as yet
+    ## NA.
+    corp(1 : n + 1 : n * n) = 1;
+
+    ## If there are indices, applied to both row and column, so that
+    ## indexed elements within one row or one column are determined up
+    ## to a multiple of a vector, find both these vectors and the
+    ## respective indices. In the same run, use them to further fill in
+    ## corp as described below.
+    for id = 1 : (cb = columns (basis))
+      if (any (idx = \
+	       all (basis(:, (1 : cb) != id) == 0, 2) & \
+	       basis(:, id) != 0))
+	vec = sign (basis(idx, id));
+
+	## Depending on "vec", single coefficients of correlation
+	## indexed by "idx" are either +1 or -1.
+	corp(idx, idx) = vec * vec.';
+      endif
+    endfor
+
+    hook.covp = covp;
+    hook.corp = corp;
+
+  endif
+
+endfunction