clean up file (remove unused variables, fprintf instead of disp(sprintf()))
parent
f118970736
commit
42842a5afc
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@ -23,7 +23,7 @@ function myoutput=PosteriorIRF_core1(myinputs,fpar,B,whoiam, ThisMatlab)
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% SPECIAL REQUIREMENTS.
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% None.
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%
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% Copyright (C) 2006-2018 Dynare Team
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% Copyright (C) 2006-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -70,10 +70,8 @@ NumberOfIRFfiles_dsgevar=myinputs.NumberOfIRFfiles_dsgevar;
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ifil2=myinputs.ifil2;
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if options_.dsge_var
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gend=myinputs.gend;
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nvobs=myinputs.nvobs;
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NumberOfParametersPerEquation = myinputs.NumberOfParametersPerEquation;
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NumberOfLags = myinputs.NumberOfLags;
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NumberOfLagsTimesNvobs = myinputs.NumberOfLagsTimesNvobs;
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Companion_matrix = myinputs.Companion_matrix;
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stock_irf_bvardsge = zeros(options_.irf,nvobs,M_.exo_nbr,MAX_nirfs_dsgevar);
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@ -194,7 +192,7 @@ while fpar<B
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end
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if MAX_nirfs_dsgevar
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IRUN = IRUN+1;
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[fval,info,~,~,~,~,~,PHI,SIGMAu,iXX] = dsge_var_likelihood(deep',dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
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[~,~,~,~,~,~,~,PHI,SIGMAu,iXX] = dsge_var_likelihood(deep',dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,bounds,oo_);
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dsge_prior_weight = M_.params(strmatch('dsge_prior_weight', M_.param_names));
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DSGE_PRIOR_WEIGHT = floor(dataset_.nobs*(1+dsge_prior_weight));
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SIGMA_inv_upper_chol = chol(inv(SIGMAu*dataset_.nobs*(dsge_prior_weight+1)));
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@ -216,7 +214,7 @@ while fpar<B
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if dsge_prior_weight > 0
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Atheta(oo_.dr.order_var,M_.exo_names_orig_ord) = oo_.dr.ghu*sqrt(M_.Sigma_e);
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A0 = Atheta(bayestopt_.mfys,:);
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[OMEGAstar,SIGMAtr] = qr2(A0');
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OMEGAstar = qr2(A0');
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end
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SIGMAu_chol = chol(SIGMAu_draw)';
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SIGMAtrOMEGA = SIGMAu_chol*OMEGAstar';
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@ -245,7 +243,6 @@ while fpar<B
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end
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NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
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IRUN =0;
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stock_irf_dsgevar = zeros(options_.irf,dataset_.vobs,M_.exo_nbr,MAX_nirfs_dsgevar);
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end
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end
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if irun == MAX_nirfs_dsge || irun == B || fpar == B
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@ -28,12 +28,11 @@ if ~options_.noprint
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disp_steady_state(M_,oo_)
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for i=M_.orig_endo_nbr:M_.endo_nbr
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if strmatch('mult_', M_.endo_names{i})
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disp(sprintf('%s \t\t %g', M_.endo_names{i}, oo_.dr.ys(i)));
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fprintf('%s \t\t %g\n', M_.endo_names{i}, oo_.dr.ys(i));
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end
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end
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end
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oo_.planner_objective_value = evaluate_planner_objective(M_,options_,oo_);
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options_ = oldoptions;
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@ -15,7 +15,7 @@ function [g,grad,hess,flag] = moment_function(xparams,sample_moments,dataset,opt
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% SPECIAL REQUIREMENTS
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% The user has to provide a file where the moment conditions are defined.
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% Copyright (C) 2010-2017 Dynare Team
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% Copyright (C) 2010-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -92,7 +92,7 @@ else% parallel mode.
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error('The parallel version of SMM estimation is not implemented for non unix platforms!')
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end
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job_number = 1;% Remark. First job is for the master.
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[Junk,hostname] = unix('hostname --fqdn');
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[~,hostname] = unix('hostname --fqdn');
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hostname = deblank(hostname);
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for i=1:length(parallel)
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machine = deblank(parallel(i).machine);
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@ -16,7 +16,7 @@ function osr_res = osr1(i_params,i_var,weights)
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% Uses Newton-type optimizer csminwel to directly solve quadratic
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% osr-problem
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%
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% Copyright (C) 2005-2018 Dynare Team
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% Copyright (C) 2005-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -35,10 +35,6 @@ function osr_res = osr1(i_params,i_var,weights)
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global M_ oo_ options_ it_
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klen = M_.maximum_lag + M_.maximum_lead + 1;
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iyv = M_.lead_lag_incidence';
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iyv = iyv(:);
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iyr0 = find(iyv) ;
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it_ = M_.maximum_lag + 1 ;
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osr_res.error_indicator = 1; %initialize indicator
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@ -84,8 +80,6 @@ if isfield(options_.osr,'maxit') || isfield(options_.osr,'tolf')
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end
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end
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exe =zeros(M_.exo_nbr,1);
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oo_.dr = set_state_space(oo_.dr,M_,options_);
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@ -99,7 +93,7 @@ inv_order_var = oo_.dr.inv_order_var;
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%extract unique entries of covariance
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i_var=unique(i_var);
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%% do initial checks
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[loss,info,exit_flag,vx]=osr_obj(t0,i_params,inv_order_var(i_var),weights(i_var,i_var));
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[loss,info]=osr_obj(t0,i_params,inv_order_var(i_var),weights(i_var,i_var));
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if info~=0
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print_info(info, options_.noprint, options_);
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else
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@ -129,7 +123,7 @@ else
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error('OSR: OSR with bounds on parameters requires a constrained optimizer, i.e. opt_algo= 1,2,5, or 9.')
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end
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%%do actual optimization
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[p, f, exitflag] = dynare_minimize_objective(str2func('osr_obj'),t0,options_.osr.opt_algo,options_,M_.osr.param_bounds,M_.param_names(i_params),[],[], i_params,...
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[p, f] = dynare_minimize_objective(str2func('osr_obj'),t0,options_.osr.opt_algo,options_,M_.osr.param_bounds,M_.param_names(i_params),[],[], i_params,...
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inv_order_var(i_var),weights(i_var,i_var));
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end
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@ -144,9 +138,9 @@ if ~options_.noprint
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disp('OPTIMAL VALUE OF THE PARAMETERS:')
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skipline()
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for i=1:np
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disp(sprintf('%16s %16.6g\n', M_.param_names{i_params(i)}, p(i)))
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fprintf('%16s %16.6g\n\n', M_.param_names{i_params(i)}, p(i));
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end
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disp(sprintf('Objective function : %16.6g\n',f));
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fprintf('Objective function : %16.6g\n\n',f);
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skipline()
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end
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[oo_.dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
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@ -15,7 +15,7 @@ function [r,flag] = smm_objective(xparams,sample_moments,weighting_matrix,option
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% SPECIAL REQUIREMENTS
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% The user has to provide a file where the moment conditions are defined.
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% Copyright (C) 2010-2017 Dynare Team
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% Copyright (C) 2010-2019 Dynare Team
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%
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% This file is part of Dynare.
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%
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@ -75,7 +75,7 @@ save('estimated_parameters.mat','xparams');
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% Check for local determinacy of the deterministic steady state.
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noprint = options_.noprint; options_.noprint = 1;
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[eigval,local_determinacy_and_stability,info] = check(M_,options_,oo_); options_.noprint = noprint;
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[~,local_determinacy_and_stability,info] = check(M_,options_,oo_); options_.noprint = noprint;
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if ~local_determinacy_and_stability
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r = priorObjectiveValue * (1+info(2));
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flag = 0;
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@ -100,7 +100,7 @@ else% parallel mode.
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error('The parallel version of SMM estimation is not implemented for non unix platforms!')
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end
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job_number = 1;% Remark. First job is for the master.
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[Junk,hostname] = unix('hostname --fqdn');
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[~,hostname] = unix('hostname --fqdn');
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hostname = deblank(hostname);
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for i=1:length(parallel)
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machine = deblank(parallel(i).machine);
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