csminwel1.m and csminwel1.m: cosmetic changes
Johannes Pfeifer
parent
a57f81b3aa
commit
497c6bd1b1
|
|
@ -38,7 +38,7 @@ function [fhat,xhat,fcount,retcode] = csminit1(fcn,x0,penalty,f0,g0,badg,H0,Verb
|
|||
% http://sims.princeton.edu/yftp/optimize/mfiles/csminit.m
|
||||
%
|
||||
% Copyright © 1993-2007 Christopher Sims
|
||||
% Copyright © 2008-2017 Dynare Team
|
||||
% Copyright © 2008-2023 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
@ -55,24 +55,14 @@ function [fhat,xhat,fcount,retcode] = csminit1(fcn,x0,penalty,f0,g0,badg,H0,Verb
|
|||
% You should have received a copy of the GNU General Public License
|
||||
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
|
||||
|
||||
%tailstr = ')';
|
||||
%for i=nargin-6:-1:1
|
||||
% tailstr=[ ',P' num2str(i) tailstr];
|
||||
%end
|
||||
%ANGLE = .03;
|
||||
ANGLE = .005;
|
||||
%THETA = .03;
|
||||
THETA = .3; %(0<THETA<.5) THETA near .5 makes long line searches, possibly fewer iterations.
|
||||
FCHANGE = 1000;
|
||||
MINLAMB = 1e-9;
|
||||
% fixed 7/15/94
|
||||
% MINDX = .0001;
|
||||
% MINDX = 1e-6;
|
||||
MINDFAC = .01;
|
||||
fcount=0;
|
||||
lambda=1;
|
||||
xhat=x0;
|
||||
f=f0;
|
||||
fhat=f0;
|
||||
g = g0;
|
||||
gnorm = norm(g);
|
||||
|
|
@ -84,34 +74,13 @@ if (gnorm < 1.e-12) && ~badg % put ~badg 8/4/94
|
|||
else
|
||||
% with badg true, we don't try to match rate of improvement to directional
|
||||
% derivative. We're satisfied just to get some improvement in f.
|
||||
%
|
||||
%if(badg)
|
||||
% dx = -g*FCHANGE/(gnorm*gnorm);
|
||||
% dxnorm = norm(dx);
|
||||
% if dxnorm > 1e12
|
||||
% disp('Bad, small gradient problem.')
|
||||
% dx = dx*FCHANGE/dxnorm;
|
||||
% end
|
||||
%else
|
||||
% Gauss-Newton step;
|
||||
%---------- Start of 7/19/93 mod ---------------
|
||||
%[v d] = eig(H0);
|
||||
%toc
|
||||
%d=max(1e-10,abs(diag(d)));
|
||||
%d=abs(diag(d));
|
||||
%dx = -(v.*(ones(size(v,1),1)*d'))*(v'*g);
|
||||
% toc
|
||||
dx = -H0*g;
|
||||
% toc
|
||||
dxnorm = norm(dx);
|
||||
if dxnorm > 1e12
|
||||
disp_verbose('Near-singular H problem.',Verbose)
|
||||
dx = dx*FCHANGE/dxnorm;
|
||||
end
|
||||
dfhat = dx'*g0;
|
||||
%end
|
||||
%
|
||||
%
|
||||
if ~badg
|
||||
% test for alignment of dx with gradient and fix if necessary
|
||||
a = -dfhat/(gnorm*dxnorm);
|
||||
|
|
@ -123,7 +92,6 @@ else
|
|||
end
|
||||
end
|
||||
disp_verbose(sprintf('Predicted improvement: %18.9f',-dfhat/2),Verbose)
|
||||
%
|
||||
% Have OK dx, now adjust length of step (lambda) until min and
|
||||
% max improvement rate criteria are met.
|
||||
done=0;
|
||||
|
|
@ -132,7 +100,6 @@ else
|
|||
lambdaMax=inf;
|
||||
lambdaPeak=0;
|
||||
fPeak=f0;
|
||||
lambdahat=0;
|
||||
while ~done
|
||||
if size(x0,2)>1
|
||||
dxtest=x0+dx'*lambda;
|
||||
|
|
@ -141,16 +108,10 @@ else
|
|||
end
|
||||
% home
|
||||
f = penalty_objective_function(dxtest,fcn,penalty,varargin{:});
|
||||
%ARGLIST
|
||||
%f = feval(fcn,dxtest,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
|
||||
% f = feval(fcn,x0+dx*lambda,P1,P2,P3,P4,P5,P6,P7,P8);
|
||||
disp_verbose(sprintf('lambda = %10.5g; f = %20.7f',lambda,f ),Verbose)
|
||||
%debug
|
||||
%disp(sprintf('Improvement too great? f0-f: %g, criterion: %g',f0-f,-(1-THETA)*dfhat*lambda))
|
||||
if f<fhat
|
||||
fhat=f;
|
||||
xhat=dxtest;
|
||||
lambdahat = lambda;
|
||||
end
|
||||
fcount=fcount+1;
|
||||
shrinkSignal = (~badg & (f0-f < max([-THETA*dfhat*lambda 0]))) | (badg & (f0-f) < 0) ;
|
||||
|
|
@ -162,7 +123,6 @@ else
|
|||
while lambda/factor <= lambdaPeak
|
||||
factor=factor^.6;
|
||||
end
|
||||
%if (abs(lambda)*(factor-1)*dxnorm < MINDX) || (abs(lambda)*(factor-1) < MINLAMB)
|
||||
if abs(factor-1)<MINDFAC
|
||||
if abs(lambda)<4
|
||||
retcode=2;
|
||||
|
|
@ -197,7 +157,6 @@ else
|
|||
if shrink
|
||||
shrink=0;
|
||||
factor = factor^.6;
|
||||
%if ( abs(lambda)*(factor-1)*dxnorm< MINDX ) || ( abs(lambda)*(factor-1)< MINLAMB)
|
||||
if abs(factor-1)<MINDFAC
|
||||
if abs(lambda)<4
|
||||
retcode=4;
|
||||
|
|
|
|||
|
|
@ -4,9 +4,9 @@ function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel1(fcn,x0,H0,grad,crit,nit,m
|
|||
% fcn: [string] string naming the objective function to be minimized
|
||||
% x0: [npar by 1] initial value of the parameter vector
|
||||
% H0: [npar by npar] initial value for the inverse Hessian. Must be positive definite.
|
||||
% grad: [string or empty matrix] Either a string naming a function that calculates the gradient, or the null matrix.
|
||||
% If it's null, the program calculates a numerical gradient. In this case fcn must
|
||||
% be written so that it can take a matrix argument and produce a row vector of values.
|
||||
% grad: [string or boolean] Either a string naming a function that calculates the gradient, or a boolean
|
||||
% indicating whether the function returns a gradient (column) vector. If false, the program
|
||||
% calculates a numerical gradient.
|
||||
% crit: [scalar] Convergence criterion. Iteration will cease when it proves impossible to improve the
|
||||
% function value by more than crit.
|
||||
% nit: [scalar] Maximum number of iterations.
|
||||
|
|
@ -42,7 +42,7 @@ function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel1(fcn,x0,H0,grad,crit,nit,m
|
|||
% http://sims.princeton.edu/yftp/optimize/mfiles/csminwel.m
|
||||
%
|
||||
% Copyright © 1993-2007 Christopher Sims
|
||||
% Copyright © 2006-2021 Dynare Team
|
||||
% Copyright © 2006-2023 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
|
|||
Loading…
Reference in New Issue