193 lines
6.8 KiB
Matlab
193 lines
6.8 KiB
Matlab
function [fhat,xhat,fcount,retcode] = csminit1(fcn,x0,penalty,f0,g0,badg,H0,Verbose,varargin)
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% [fhat,xhat,fcount,retcode] = csminit1(fcn,x0,penalty,f0,g0,badg,H0,Verbose,varargin)
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%
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% Inputs:
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% fcn: [string] string naming the objective function to be minimized
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% x0: [npar by 1] initial value of the parameter vector
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% penalty: [scalar] variable penalty in case of failure of objective function
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% f0: [scalar] initial value of the fucntion
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% g0: [npar by 1] initial value of the gradient vector
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% badg [scalar] indicator for problem in gradient computation
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% H0: [npar by npar] initial value for the inverse Hessian. Must be positive definite.
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% Verbose: [scalar] indicator for verbose computations
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% varargin: Optional additional inputs that get handed off to fcn each
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% time it is called.
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% Outputs:
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% fhat: [scalar] function value at minimum
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% xhat: [npar by 1] parameter vector at minimum
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% fcount [scalar] function iteration count upon termination
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% retcode [scalar] 0: normal step
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% 1: zero gradient.
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% 5: largest step still improves too fast.
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% 2,4: back and forth adjustment of stepsize didn't finish.
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% 3: smallest stepsize still improves too slow
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% 6: no improvement found
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%---------------------
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% Modified 7/22/96 to omit variable-length P list, for efficiency and compilation.
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% Places where the number of P's need to be altered or the code could be returned to
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% its old form are marked with ARGLIST comments.
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%
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% Fixed 7/17/93 to use inverse-hessian instead of hessian itself in bfgs
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% update.
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%
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% Fixed 7/19/93 to flip eigenvalues of H to get better performance when
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% it's not psd.
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%
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% Original file downloaded from:
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% http://sims.princeton.edu/yftp/optimize/mfiles/csminit.m
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%
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% Copyright © 1993-2007 Christopher Sims
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% Copyright © 2008-2023 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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ANGLE = .005;
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THETA = .3; %(0<THETA<.5) THETA near .5 makes long line searches, possibly fewer iterations.
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FCHANGE = 1000;
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MINLAMB = 1e-9;
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MINDFAC = .01;
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fcount=0;
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lambda=1;
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xhat=x0;
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fhat=f0;
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g = g0;
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gnorm = norm(g);
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%
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if (gnorm < 1.e-12) && ~badg % put ~badg 8/4/94
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retcode =1;
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dxnorm=0;
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% gradient convergence
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else
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% with badg true, we don't try to match rate of improvement to directional
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% derivative. We're satisfied just to get some improvement in f.
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dx = -H0*g;
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dxnorm = norm(dx);
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if dxnorm > 1e12
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disp_verbose('Near-singular H problem.',Verbose)
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dx = dx*FCHANGE/dxnorm;
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end
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dfhat = dx'*g0;
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if ~badg
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% test for alignment of dx with gradient and fix if necessary
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a = -dfhat/(gnorm*dxnorm);
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if a<ANGLE
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dx = dx - (ANGLE*dxnorm/gnorm+dfhat/(gnorm*gnorm))*g;
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dfhat = dx'*g;
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dxnorm = norm(dx);
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disp_verbose(sprintf('Correct for low angle: %g',a),Verbose)
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end
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end
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disp_verbose(sprintf('Predicted improvement: %18.9f',-dfhat/2),Verbose)
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% Have OK dx, now adjust length of step (lambda) until min and
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% max improvement rate criteria are met.
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done=0;
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factor=3;
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shrink=1;
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lambdaMax=inf;
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lambdaPeak=0;
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fPeak=f0;
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while ~done
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if size(x0,2)>1
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dxtest=x0+dx'*lambda;
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else
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dxtest=x0+dx*lambda;
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end
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% home
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f = penalty_objective_function(dxtest,fcn,penalty,varargin{:});
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disp_verbose(sprintf('lambda = %10.5g; f = %20.7f',lambda,f ),Verbose)
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if f<fhat
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fhat=f;
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xhat=dxtest;
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end
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fcount=fcount+1;
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shrinkSignal = (~badg & (f0-f < max([-THETA*dfhat*lambda 0]))) | (badg & (f0-f) < 0) ;
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growSignal = ~badg & ( (lambda > 0) & (f0-f > -(1-THETA)*dfhat*lambda) );
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if shrinkSignal && ( (lambda>lambdaPeak) || (lambda<0) )
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if (lambda>0) && ((~shrink) || (lambda/factor <= lambdaPeak))
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shrink=1;
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factor=factor^.6;
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while lambda/factor <= lambdaPeak
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factor=factor^.6;
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end
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if abs(factor-1)<MINDFAC
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if abs(lambda)<4
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retcode=2;
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else
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retcode=7;
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end
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done=1;
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end
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end
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if (lambda<lambdaMax) && (lambda>lambdaPeak)
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lambdaMax=lambda;
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end
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lambda=lambda/factor;
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if abs(lambda) < MINLAMB
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if (lambda > 0) && (f0 <= fhat)
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% try going against gradient, which may be inaccurate
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if Verbose
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lambda = -lambda*factor^6
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else
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lambda = -lambda*factor^6;
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end
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else
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if lambda < 0
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retcode = 6;
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else
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retcode = 3;
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end
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done = 1;
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end
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end
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elseif (growSignal && lambda>0) || (shrinkSignal && ((lambda <= lambdaPeak) && (lambda>0)))
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if shrink
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shrink=0;
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factor = factor^.6;
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if abs(factor-1)<MINDFAC
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if abs(lambda)<4
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retcode=4;
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else
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retcode=7;
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end
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done=1;
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end
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end
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if ( f<fPeak ) && (lambda>0)
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fPeak=f;
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lambdaPeak=lambda;
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if lambdaMax<=lambdaPeak
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lambdaMax=lambdaPeak*factor*factor;
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end
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end
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lambda=lambda*factor;
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if abs(lambda) > 1e20
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retcode = 5;
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done =1;
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end
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else
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done=1;
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if factor < 1.2
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retcode=7;
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else
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retcode=0;
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end
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end
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end
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end
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disp_verbose(sprintf('Norm of dx %10.5g', dxnorm),Verbose)
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