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* Changed numgrad.m. If fcn(x+h) is not well defined (for instance cost_flag=0 because of BK conditions) we compute the gradient using (fcn(x)-fcn(x-h))/h instead of the original formula (fcn(x+h)-fcn(x))/h. 

* Added function numgrad3.m. This new function uses a three point formula to compute the gradient. By default Dynare uses the two point formula. By setting options_.gradient_method=3 Dynare switches to the three point formula. Note that an input argument has been added to csminwel.
* Added automatic detection of needed constant in dsge-var model (may be problematic is some cases)

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1935 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
adjemian 2008-07-07 12:58:13 +00:00
parent 7f927eff00
commit 27886047cf
6 changed files with 116 additions and 60 deletions
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79
matlab/csminwel.m
View File

@ -1,5 +1,5 @@
function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel(fcn,x0,H0,grad,crit,nit,varargin)
%[fhat,xhat,ghat,Hhat,itct,fcount,retcodehat] = csminwel(fcn,x0,H0,grad,crit,nit,varargin)
function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel(fcn,x0,H0,grad,crit,nit,method,varargin)
%[fhat,xhat,ghat,Hhat,itct,fcount,retcodehat] = csminwel(fcn,x0,H0,grad,crit,nit,method,varargin)
% fcn: string naming the objective function to be minimized
% x0: initial value of the parameter vector
% H0: initial value for the inverse Hessian. Must be positive definite.
@ -9,6 +9,7 @@ function [fh,xh,gh,H,itct,fcount,retcodeh] = csminwel(fcn,x0,H0,grad,crit,nit,va
% crit: Convergence criterion. Iteration will cease when it proves impossible to improve the
% function value by more than crit.
% nit: Maximum number of iterations.
% method: integer scalar, 2 or 3 points formula.
% varargin: A list of optional length of additional parameters that get handed off to fcn each
% time it is called.
% Note that if the program ends abnormally, it is possible to retrieve the current x,
@ -37,25 +38,21 @@ snit=100;
% tailstr=[ ',P' num2str(i) tailstr];
% stailstr=[' P' num2str(i) stailstr];
%end
f0 = feval(fcn,x0,varargin{:});
%ARGLIST
%f0 = feval(fcn,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
% disp('first fcn in csminwel.m ----------------') % Jinill on 9/5/95
if f0 > 1e50, disp('Bad initial parameter.'), return, end
[f0,cost_flag] = feval(fcn,x0,varargin{:});
if ~cost_flag
disp('Bad initial parameter.')
return
end
if NumGrad
if length(grad)==0
[g badg] = numgrad(fcn,x0, varargin{:});
%ARGLIST
%[g badg] = numgrad(fcn,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
else
badg=any(find(grad==0));
g=grad;
end
%numgrad(fcn,x0,P1,P2,P3,P4);
if method==2
[g,badg] = numgrad(fcn,x0, varargin{:});
elseif method==3
[g,badg] = numgrad3(fcn,x0, varargin{:});
end
else
[g badg] = feval(grad,x0,varargin{:});
%ARGLIST
%[g badg] = feval(grad,x0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,P11,P12,P13);
[g,badg] = feval(grad,x0,varargin{:});
end
retcode3=101;
x=x0;
@ -93,15 +90,13 @@ while ~done
wall1=1; badg1=1;
else
if NumGrad
[g1 badg1] = numgrad(fcn, x1,varargin{:});
%ARGLIST
%[g1 badg1] = numgrad(fcn, x1,P1,P2,P3,P4,P5,P6,P7,P8,P9,...
% P10,P11,P12,P13);
if method == 2
[g1 badg1] = numgrad(fcn, x1,varargin{:});
elseif method == 3
[g1 badg1] = numgrad3(fcn, x1,varargin{:});
end
else
[g1 badg1] = feval(grad,x1,varargin{:});
%ARGLIST
%[g1 badg1] = feval(grad, x1,P1,P2,P3,P4,P5,P6,P7,P8,P9,...
% P10,P11,P12,P13);
end
wall1=badg1;
% g1
@ -126,15 +121,13 @@ while ~done
wall2=1; badg2=1;
else
if NumGrad
[g2 badg2] = numgrad(fcn, x2,varargin{:});
%ARGLIST
%[g2 badg2] = numgrad(fcn, x2,P1,P2,P3,P4,P5,P6,P7,P8,...
% P9,P10,P11,P12,P13);
if method==2
[g2 badg2] = numgrad(fcn, x2,varargin{:});
elseif method==3
[g2 badg2] = numgrad3(fcn, x2,varargin{:});
end
else
[g2 badg2] = feval(grad,x2,varargin{:});
%ARGLIST
%[g2 badg2] = feval(grad,x2,P1,P2,P3,P4,P5,P6,P7,P8,...
% P9,P10,P11,P12,P13);
end
wall2=badg2;
% g2
@ -160,15 +153,13 @@ while ~done
wall3=1; badg3=1;
else
if NumGrad
[g3 badg3] = numgrad(fcn, x3,varargin{:});
%ARGLIST
%[g3 badg3] = numgrad(fcn, x3,P1,P2,P3,P4,P5,P6,P7,P8,...
% P9,P10,P11,P12,P13);
if method==2
[g3 badg3] = numgrad(fcn, x3,varargin{:});
elseif method==3
[g3 badg3] = numgrad3(fcn, x3,varargin{:});
end
else
[g3 badg3] = feval(grad,x3,varargin{:});
%ARGLIST
%[g3 badg3] = feval(grad,x3,P1,P2,P3,P4,P5,P6,P7,P8,...
% P9,P10,P11,P12,P13);
end
wall3=badg3;
% g3
@ -224,7 +215,11 @@ while ~done
end
if nogh
if NumGrad
[gh badgh] = numgrad(fcn,xh,varargin{:});
if method==2
[gh,badgh] = numgrad(fcn,xh,varargin{:});
elseif method==3
[gh,badgh] = numgrad3(fcn,xh,varargin{:});
end
else
[gh badgh] = feval(grad, xh,varargin{:});
end
@ -274,4 +269,4 @@ while ~done
badg=badgh;
end
% what about making an m-file of 10 lines including numgrad.m
% since it appears three times in csminwel.m
% since it appears three times in csminwel.m

19
matlab/dynare_estimation.m
View File

@ -1,5 +1,4 @@
function dynare_estimation(var_list_)
% function dynare_estimation(var_list_)
% runs the estimation of the model
%
@ -17,8 +16,7 @@ function dynare_estimation(var_list_)
global M_ options_ oo_ estim_params_
global bayestopt_ dsge_prior_weight
global bayestopt_
options_.varlist = var_list_;
options_.lgyidx2varobs = zeros(size(M_.endo_names,1),1);
@ -259,9 +257,16 @@ else% if the steady state file is not provided.
[dd,info] = resol(oo_.steady_state,0);
oo_.steady_state = dd.ys; clear('dd');
end
if all(abs(oo_.steady_state(bayestopt_.mfys))<1e-9)
disp('no constant')
options_.noconstant = 1;
else
options_.noconstant = 0;
end
%% compute sample moments if needed (bvar-dsge)
if options_.bvar_dsge~isempty(strmatch('dsge_prior_weight',M_.param_names))
if options_.bvar_dsge
if options_.noconstant
evalin('base',...
['[mYY,mXY,mYX,mXX,Ydata,Xdata] = ' ...
@ -337,7 +342,7 @@ if options_.mode_compute > 0 & options_.posterior_mode_estimation
if isfield(options_,'optim_opt')
eval(['optim_options = optimset(optim_options,' options_.optim_opt ');']);
end
if isempty(strmatch('dsge_prior_weight',M_.param_names))
if ~options_.bvar_dsge
[xparam1,fval,exitflag] = fminunc(fh,xparam1,optim_options,gend,data);
else
[xparam1,fval,exitflag] = fminunc(fh,xparam1,optim_options,gend);
@ -349,12 +354,12 @@ if options_.mode_compute > 0 & options_.posterior_mode_estimation
verbose = 2;
if ~options_.bvar_dsge
[fval,xparam1,grad,hessian_csminwel,itct,fcount,retcodehat] = ...
csminwel('DsgeLikelihood',xparam1,H0,[],crit,nit,gend,data);
csminwel('DsgeLikelihood',xparam1,H0,[],crit,nit,options_.gradient_method,gend,data);
disp(sprintf('Objective function at mode: %f',fval))
disp(sprintf('Objective function at mode: %f',DsgeLikelihood(xparam1,gend,data)))
else
[fval,xparam1,grad,hessian_csminwel,itct,fcount,retcodehat] = ...
csminwel('DsgeVarLikelihood',xparam1,H0,[],crit,nit,gend);
csminwel('DsgeVarLikelihood',xparam1,H0,[],crit,nit,options_.gradient_method,gend);
disp(sprintf('Objective function at mode: %f',fval))
disp(sprintf('Objective function at mode: %f',DsgeVarLikelihood(xparam1,gend)))
end

5
matlab/global_initialization.m
View File

@ -50,8 +50,8 @@ function global_initialization()
options_.varlag = 4;
% Optimization algorithm [6] gmhmaxlik
options_.Opt6Iter = 3;
options_.Opt6Numb = 100000;
options_.Opt6Iter = 2;
options_.Opt6Numb = 5000;
% Graphics
options_.graphics.nrows = 3;
@ -148,6 +148,7 @@ function global_initialization()
options_.subdraws = [];
options_.unit_root_vars = [];
options_.use_mh_covariance_matrix = 0;
options_.gradient_method = 2;
% Misc
options_.conf_sig = 0.6;

26
matlab/numgrad.m
View File

@ -1,7 +1,7 @@
function [g, badg] = numgrad(fcn,x,varargin)
% function [g badg] = numgrad(fcn,xvarargin)
%
delta = 1e-6;
delta = 1e-6;
%delta=1e-2;
n=length(x);
tvec=delta*eye(n);
@ -15,29 +15,40 @@ g=zeros(n,1);
%end
%f0 = eval([fcn '(x' tailstr]); % Is there a way not to do this?
%---------------------------------------------------------------^yes
f0 = eval([fcn '(x,varargin{:})']);
[f0,cost_flag] = feval(fcn, x, varargin{:});
%f0 = eval([fcn '(x,varargin{:})']);
% disp(' first fcn in numgrad.m ------------------')
%home
% disp('numgrad.m is working. ----') % Jiinil on 9/5/95
% sizex=size(x),sizetvec=size(tvec),x, % Jinill on 9/6/95
badg=0;
goog=1;% stepan 07/07/2008
scale=1; % stepan 07/07/2008
for i=1:n
scale=1; % originally 1
% i,tveci=tvec(:,i)% ,plus=x+scale*tvec(:,i) % Jinill Kim on 9/6/95
if size(x,1)>size(x,2)
tvecv=tvec(i,:);
else
tvecv=tvec(:,i);
end
g0 = (eval([fcn '(x+scale*tvecv'', varargin{:})']) - f0) ...
/(scale*delta);
[fh,cost_flag] = feval(fcn, x+scale*transpose(tvecv), varargin{:});% stepan 07/07/2008
if cost_flag% stepan 07/07/2008
g0 = (fh - f0) / (scale*delta);
else
[fh,cost_flag] = feval(fcn, x-scale*transpose(tvecv), varargin{:});
if cost_flag
g0 = (f0-fh) / (scale*delta);
else
goog=0;
end
end
% disp(' fcn in the i=1:n loop of numgrad.m ------------------')% Jinill 9/6/95
% disp(' and i is') % Jinill
% i % Jinill
% fprintf('Gradient w.r.t. %3d: %10g\n',i,g0) %see below Jinill 9/6/95
% -------------------------- special code to essentially quit here
% absg0=abs(g0) % Jinill on 9/6/95
if abs(g0)< 1e15
if goog && abs(g0)< 1e15 % stepan 07/07/2008
g(i)=g0;
% disp('good gradient') % Jinill Kim
else
@ -94,5 +105,4 @@ end
% end
%end
%save g.dat g x f0
%eval(['save g g x f0 ' stailstr]);
%eval(['save g g x f0 ' stailstr]);

45
matlab/numgrad3.m Normal file
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@ -0,0 +1,45 @@
function [g, badg] = numgrad3(fcn,x,varargin)
% Computes the gradient of the objective function fcn using a three point
% formula if possible.
%
% Adapted from Sims' numgrad routine.
%
% part of DYNARE, copyright Dynare Team (2008)
% Gnu Public License.
delta = 1e-6;
n=length(x);
tvec=delta*eye(n);
g=zeros(n,1);
[f0,cost_flag] = feval(fcn, x, varargin{:});
badg=0;
goog=1;
scale=1;
for i=1:n
if size(x,1)>size(x,2)
tvecv=tvec(i,:);
else
tvecv=tvec(:,i);
end
[f1,cost_flag1] = feval(fcn, x+scale*transpose(tvecv), varargin{:});
[f2,cost_flag2] = feval(fcn, x-scale*transpose(tvecv), varargin{:});
if cost_flag1 && cost_flag2
g0 = (f1 - f2) / (2*scale*delta);
elseif cost_flag1==1 && cost_flag2==0
g0 = (f1-f0) / (scale*delta);
elseif cost_flag1==0 && cost_flag2==1
g0 = (f0-f2) / (scale*delta);
else
goog=0;
end
if goog && abs(g0)< 1e15
g(i)=g0;
else
disp('bad gradient ------------------------')
g(i)=0;
badg=1;
end
end

2
matlab/osr1.m
View File

@ -45,7 +45,7 @@ function osr1(i_params,i_var,weights)
nit = 1000;
verbose = 2;
[f,p]=csminwel('osr_obj',t0,H0,[],crit,nit,i_params,...
[f,p]=csminwel('osr_obj',t0,H0,[],crit,nit,options_.gradient_method,i_params,...
inv_order_var(i_var),weights(i_var,i_var));
% options = optimset('fminunc');