diff --git a/matlab/CutSample.m b/matlab/CutSample.m
index 5a3e940196f77dd312b14c8438276d71db4ce375..e0a2b16ecb3170ca7b70a38c54e3c9cceb7521d5 100644
--- a/matlab/CutSample.m
+++ b/matlab/CutSample.m
@@ -67,4 +67,4 @@ fprintf('MH: Total number of generated MH files: %d.\n',TotalNumberOfMhFiles);
fprintf('MH: I''ll use mh-files %d to %d.\n',FirstMhFile,TotalNumberOfMhFiles);
fprintf('MH: In MH-file number %d I''ll start at line %d.\n',FirstMhFile,FirstLine);
fprintf('MH: Finally I keep %d draws.\n',TotalNumberOfMhDraws-FirstDraw);
-disp(' ');
+skipline()
diff --git a/matlab/GetPosteriorParametersStatistics.m b/matlab/GetPosteriorParametersStatistics.m
index cb6ba4219815513272b12e88627d8e895ee506e0..04ca6c86cc7c830e3b383532cac8c3685a6b1362 100644
--- a/matlab/GetPosteriorParametersStatistics.m
+++ b/matlab/GetPosteriorParametersStatistics.m
@@ -62,7 +62,10 @@ header_width = row_header_width(M_,estim_params_,bayestopt_);
tit2 = sprintf('%-*s %10s %10s %16s %6s %10s\n',header_width+2,' ','prior mean','post. mean','conf. interval','prior','pstdev');
pformat = '%-*s %10.3f %10.4f %10.4f %8.4f %6s %10.4f';
-disp(' ');disp(' ');disp('ESTIMATION RESULTS');disp(' ');
+skipline(2)
+disp('ESTIMATION RESULTS')
+skipline()
+
try
disp(sprintf('Log data density is %f.',oo_.MarginalDensity.ModifiedHarmonicMean))
catch
@@ -74,7 +77,7 @@ if np
if TeX
fid = TeXBegin(OutputDirectoryName,M_.fname,1,type);
end
- disp(' ')
+ skipline()
disp(type)
disp(tit2)
ip = nvx+nvn+ncx+ncn+1;
@@ -120,7 +123,7 @@ if nvx
fid = TeXBegin(OutputDirectoryName,M_.fname,2,'standard deviation of structural shocks');
end
ip = 1;
- disp(' ')
+ skipline()
disp('standard deviation of shocks')
disp(tit2)
for i=1:nvx
@@ -165,7 +168,7 @@ if nvn
if TeX
fid = TeXBegin(OutputDirectoryName,M_.fname,3,'standard deviation of measurement errors');
end
- disp(' ')
+ skipline()
disp('standard deviation of measurement errors')
disp(tit2)
ip = nvx+1;
@@ -207,7 +210,7 @@ if ncx
if TeX
fid = TeXBegin(OutputDirectoryName,M_.fname,4,'correlation of structural shocks');
end
- disp(' ')
+ skipline()
disp('correlation of shocks')
disp(tit2)
ip = nvx+nvn+1;
@@ -261,7 +264,7 @@ if ncn
if TeX
fid = TeXBegin(OutputDirectoryName,M_.fname,5,'correlation of measurement errors');
end
- disp(' ')
+ skipline()
disp('correlation of measurement errors')
disp(tit2)
ip = nvx+nvn+ncx+1;
diff --git a/matlab/McMCDiagnostics.m b/matlab/McMCDiagnostics.m
index 7e9023eb2cd607a87567f3704c1ce8240f7d57dd..d4a26cb8c353e75a26758711e56294c8c8d7e9ad 100644
--- a/matlab/McMCDiagnostics.m
+++ b/matlab/McMCDiagnostics.m
@@ -131,7 +131,7 @@ else
end
UDIAG(:,[2 4 6],:) = UDIAG(:,[2 4 6],:)/nblck;
-disp(' ')
+skipline()
clear pmet temp moyenne CSUP CINF csup cinf n linea iter tmp;
pages = floor(npar/3);
k = 0;
diff --git a/matlab/bvar_density.m b/matlab/bvar_density.m
index 6d58fad4bdfd2d81e4842469530e6eb0baac9baf..665a9dae5c9dc4799eab80c9d48348da6259cba9 100644
--- a/matlab/bvar_density.m
+++ b/matlab/bvar_density.m
@@ -39,10 +39,10 @@ for nlags = 1:maxnlags
log_dnsty = posterior_int - prior_int - 0.5*ny*lik_nobs*log(2*pi);
- disp(' ')
+ skipline()
fprintf('The marginal log density of the BVAR(%g) model is equal to %10.4f\n', ...
nlags, log_dnsty);
- disp(' ')
+ skipline()
end
diff --git a/matlab/bvar_forecast.m b/matlab/bvar_forecast.m
index 3ee4aad953c8e323775d50ff0062bfdc8efcc723..03100c053000b06ec27695773110a76e7500f5de 100644
--- a/matlab/bvar_forecast.m
+++ b/matlab/bvar_forecast.m
@@ -94,10 +94,10 @@ while d <= options_.bvar_replic
end
if p > 0
- disp(' ')
+ skipline()
disp(['Some of the VAR models sampled from the posterior distribution'])
disp(['were found to be explosive (' num2str(p/options_.bvar_replic) ' percent).'])
- disp(' ')
+ skipline()
end
% Plot graphs
diff --git a/matlab/bvar_irf.m b/matlab/bvar_irf.m
index b46799f6afec66acec9fb30d991513b52c806381..d742915d7c7ce01ff1791969f4dc4d6db91030a9 100644
--- a/matlab/bvar_irf.m
+++ b/matlab/bvar_irf.m
@@ -92,10 +92,10 @@ for draw=1:options_.bvar_replic
end
if p > 0
- disp(' ')
+ skipline()
disp(['Some of the VAR models sampled from the posterior distribution'])
disp(['were found to be explosive (' int2str(p) ' samples).'])
- disp(' ')
+ skipline()
end
posterior_mean_irfs = mean(sampled_irfs,4);
diff --git a/matlab/check.m b/matlab/check.m
index 8c7ad94fff745ee8d6ccddb57ff50e7b86946de3..a2afc7b9f02f07d7fb085c362ff535e0ee66f95f 100644
--- a/matlab/check.m
+++ b/matlab/check.m
@@ -96,18 +96,18 @@ if (nyf == n_explod) && (dr.full_rank)
end
if options.noprint == 0
- disp(' ')
+ skipline()
disp('EIGENVALUES:')
disp(sprintf('%16s %16s %16s\n','Modulus','Real','Imaginary'))
z=[m_lambda real(eigenvalues_(i)) imag(eigenvalues_(i))]';
disp(sprintf('%16.4g %16.4g %16.4g\n',z))
disp(sprintf('\nThere are %d eigenvalue(s) larger than 1 in modulus ', n_explod));
disp(sprintf('for %d forward-looking variable(s)',nyf));
- disp(' ')
+ skipline()
if result
disp('The rank condition is verified.')
else
disp('The rank conditions ISN''T verified!')
end
- disp(' ')
+ skipline()
end
diff --git a/matlab/check_list_of_variables.m b/matlab/check_list_of_variables.m
index 75d83f7dc110ca887964d4577e46087f94cf807b..415e8759e332dbbd0c5947fa781c1b770970c099 100644
--- a/matlab/check_list_of_variables.m
+++ b/matlab/check_list_of_variables.m
@@ -45,9 +45,9 @@ if options_.dsge_var && options_.bayesian_irf
msg = 1;
end
if msg
- disp(' ')
+ skipline()
disp('Posterior IRFs will be computed for all observed variables.')
- disp(' ')
+ skipline()
end
end
varlist = options_.varobs;
@@ -55,7 +55,7 @@ if options_.dsge_var && options_.bayesian_irf
end
if isempty(varlist)
- disp(' ')
+ skipline()
disp(['You did not declare endogenous variables after the estimation/calib_smoother command.'])
cas = [];
if options_.bayesian_irf
@@ -99,14 +99,13 @@ if isempty(varlist)
else
choice = [];
while isempty(choice)
- disp(' ')
- disp(' ')
+ skipline(2)
disp('Choose one of the following options:')
- disp(' ')
+ skipline()
disp(' [1] Consider all the endogenous variables.')
disp(' [2] Consider all the observed endogenous variables.')
disp(' [3] Stop Dynare and change the mod file.')
- disp(' ')
+ skipline()
choice = input('options [default is 1] = ');
if isempty(choice)
choice=1;
@@ -118,9 +117,9 @@ if isempty(varlist)
elseif choice==3
varlist = NaN;
else
- disp('')
+ skipline()
disp('YOU HAVE TO ANSWER 1, 2 or 3!')
- disp('')
+ skipline()
end
end
end
@@ -128,7 +127,7 @@ if isempty(varlist)
if isnan(varlist)
edit([M_.fname '.mod'])
end
- disp('')
+ skipline()
end
diff --git a/matlab/disp_identification.m b/matlab/disp_identification.m
index 0badae9767ea40b34b2d5c5e5c31217647981d31..5bdb3e8e558122acf7b7b5f7cfcb6848ed9efccc 100644
--- a/matlab/disp_identification.m
+++ b/matlab/disp_identification.m
@@ -91,7 +91,7 @@ if any(idemodel.ino),
else
disp(['The rank of H (model) is deficient!' ]),
end
- disp(' ')
+ skipline()
for j=1:npar,
if any(idemodel.ind0(:,j)==0),
pno = 100*length(find(idemodel.ind0(:,j)==0))/SampleSize;
@@ -106,7 +106,7 @@ if any(idemodel.ino),
npairs=size(idemodel.jweak_pair,2);
jmap_pair=dyn_unvech(1:npairs);
jstore=[];
- disp(' ')
+ skipline()
for j=1:npairs,
iweak = length(find(idemodel.jweak_pair(:,j)));
if iweak,
@@ -120,7 +120,7 @@ if any(idemodel.ino),
end
end
- disp(' ')
+ skipline()
for j=1:npar,
iweak = length(find(idemodel.jweak(:,j)));
if iweak && ~ismember(j,jstore),
@@ -154,11 +154,11 @@ end
if ~any(idemodel.ino) && ~any(any(idemodel.ind0==0))
disp(['All parameters are identified in the model (rank of H).' ]),
- disp(' ')
+ skipline()
end
if any(idemoments.ino),
- disp(' ')
+ skipline()
disp('WARNING !!!')
if SampleSize > 1,
disp(['The rank of J (moments) is deficient for ', num2str(length(find(idemoments.ino))),' out of ',int2str(SampleSize),' MC runs!' ]),
@@ -172,7 +172,7 @@ if any(idemoments.ino),
% freqno = mean(indno)*100;
% ifreq=find(freqno);
% disp('MOMENT RANK FAILURE DUE TO COLLINEARITY OF PARAMETERS:');
- disp(' ')
+ skipline()
for j=1:npar,
if any(idemoments.ind0(:,j)==0),
pno = 100*length(find(idemoments.ind0(:,j)==0))/SampleSize;
@@ -184,7 +184,7 @@ if any(idemoments.ino),
disp([' [dJ/d(',name{j},')=0 for all J moments!]' ])
end
end
- disp(' ')
+ skipline()
npairs=size(idemoments.jweak_pair,2);
jmap_pair=dyn_unvech(1:npairs);
jstore=[];
@@ -201,7 +201,7 @@ if any(idemoments.ino),
end
end
- disp(' ')
+ skipline()
for j=1:npar,
iweak = length(find(idemoments.jweak(:,j)));
if iweak && ~ismember(j,jstore),
@@ -235,9 +235,9 @@ if any(idemoments.ino),
% end
end
if ~any(idemoments.ino) && ~any(any(idemoments.ind0==0))
- disp(' ')
+ skipline()
disp(['All parameters are identified by J moments (rank of J)' ]),
- disp(' ')
+ skipline()
end
% if ~ options_.noprint && advanced,
@@ -267,7 +267,7 @@ end
% identificaton patterns
if SampleSize==1 && advanced,
- disp(' ')
+ skipline()
disp('Press ENTER to print advanced diagnostics'), pause(5),
for j=1:size(idemoments.cosnJ,2),
pax=NaN(npar,npar);
diff --git a/matlab/disp_model_summary.m b/matlab/disp_model_summary.m
index 57b170602ba0dccf55527f605901f6c6be294662..8bd5d2b0e623d4ac0757fd8c9a4ca08cf6bbfa82 100644
--- a/matlab/disp_model_summary.m
+++ b/matlab/disp_model_summary.m
@@ -24,9 +24,9 @@ function disp_model_summary(M,dr)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-disp(' ')
+skipline()
disp('MODEL SUMMARY')
-disp(' ')
+skipline()
disp([' Number of variables: ' int2str(M.endo_nbr)])
disp([' Number of stochastic shocks: ' int2str(M.exo_nbr)])
disp([' Number of state variables: ' ...
diff --git a/matlab/disp_steady_state.m b/matlab/disp_steady_state.m
index b8eecd35a7a1f4ce21b255d8679c98722429af9d..354b0f6a455d3ecc56664cea71c85e71f2827d64 100644
--- a/matlab/disp_steady_state.m
+++ b/matlab/disp_steady_state.m
@@ -29,9 +29,9 @@ function disp_steady_state(M,oo)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-disp(' ')
+skipline()
disp('STEADY-STATE RESULTS:')
-disp(' ')
+skipline()
endo_names = M.endo_names;
steady_state = oo.steady_state;
for i=1:M.orig_endo_nbr
diff --git a/matlab/disp_th_moments.m b/matlab/disp_th_moments.m
index 6db80e8394d0fcb4b6152c6caf3b73f7f5030f32..d1a4876a296cd575dbf51016093277acdcb45767 100644
--- a/matlab/disp_th_moments.m
+++ b/matlab/disp_th_moments.m
@@ -64,7 +64,7 @@ if ~options_.noprint %options_.nomoments == 0
lh = size(labels,2)+2;
dyntable(title,headers,labels,z,lh,11,4);
if M_.exo_nbr > 1 && size(stationary_vars, 1) > 0
- disp(' ')
+ skipline()
if options_.order == 2
title='APPROXIMATED VARIANCE DECOMPOSITION (in percent)';
else
@@ -91,16 +91,16 @@ if ~options_.noprint %options_.nomoments == 0
end
if length(i1) == 0
- disp(' ')
+ skipline()
disp('All endogenous are constant or non stationary, not displaying correlations and auto-correlations')
- disp(' ')
- return;
+ skipline()
+ return
end
if options_.nocorr == 0 && size(stationary_vars, 1) > 0
corr = oo_.gamma_y{1}(i1,i1)./(sd(i1)*sd(i1)');
if ~options_.noprint,
- disp(' ')
+ skipline()
if options_.order == 2
title='APPROXIMATED MATRIX OF CORRELATIONS';
else
@@ -122,7 +122,7 @@ if options_.ar > 0 && size(stationary_vars, 1) > 0
z(:,i) = diag(oo_.gamma_y{i+1}(i1,i1));
end
if ~options_.noprint,
- disp(' ')
+ skipline()
if options_.order == 2
title='APPROXIMATED COEFFICIENTS OF AUTOCORRELATION';
else
diff --git a/matlab/display_conditional_variance_decomposition.m b/matlab/display_conditional_variance_decomposition.m
index d0b2e65369917ca1cb5a602f3a5b5571792b5ea7..7ce71478c2fceb1a342e3fd41c84c1b860d1fdd6 100644
--- a/matlab/display_conditional_variance_decomposition.m
+++ b/matlab/display_conditional_variance_decomposition.m
@@ -50,10 +50,10 @@ conditional_decomposition_array = conditional_variance_decomposition(StateSpaceM
if options_.noprint == 0
if options_.order == 2
- disp(' ')
+ skipline()
disp('APPROXIMATED CONDITIONAL VARIANCE DECOMPOSITION (in percent)')
else
- disp(' ')
+ skipline()
disp('CONDITIONAL VARIANCE DECOMPOSITION (in percent)')
end
end
diff --git a/matlab/display_estimation_results_table.m b/matlab/display_estimation_results_table.m
index 8ae45c01f3d3387cb9190d1216b18aaa500e7151..1cfcd9d3f1a3ba65f4da9215e7d317bd3e550144 100644
--- a/matlab/display_estimation_results_table.m
+++ b/matlab/display_estimation_results_table.m
@@ -44,7 +44,7 @@ ncn = estim_params_.ncn; % Covariance of the measurement innovations (number of
np = estim_params_.np ; % Number of deep parameters.
nx = nvx+nvn+ncx+ncn+np; % Total number of parameters to be estimated.
-disp(' ')
+skipline()
disp(['RESULTS FROM ' upper(table_title) ' ESTIMATION'])
LaTeXtitle=strrep(table_title,' ','_');
tstath = abs(xparam1)./stdh;
@@ -76,7 +76,7 @@ if np
eval(['oo_.' field_name '_std.parameters.' name ' = stdh(ip);']);
ip = ip+1;
end
- disp(' ')
+ skipline()
end
if nvx
ip = 1;
@@ -98,7 +98,7 @@ if nvx
eval(['oo_.' field_name '_std.shocks_std.' name ' = stdh(ip);']);
ip = ip+1;
end
- disp(' ')
+ skipline()
end
if nvn
disp('standard deviation of measurement errors')
@@ -119,7 +119,7 @@ if nvx
eval(['oo_.' field_name '_std.measurement_errors_std.' name ' = stdh(ip);']);
ip = ip+1;
end
- disp(' ')
+ skipline()
end
if ncx
@@ -144,7 +144,7 @@ if ncx
eval(['oo_.' field_name '_std.shocks_corr.' NAME ' = stdh(ip);']);
ip = ip+1;
end
- disp(' ')
+ skipline()
end
if ncn
@@ -167,7 +167,7 @@ if ncn
eval(['oo_.' field_name '_std.measurement_errors_corr.' NAME ' = stdh(ip);']);
ip = ip+1;
end
- disp(' ')
+ skipline()
end
OutputDirectoryName = CheckPath('Output',M_.dname);
diff --git a/matlab/dynare.m b/matlab/dynare.m
index fb6800c74ee41a35d6fb1132268d9256578a8444..06d81f6995e7e2bec0d9613038d2e7cb06882fa5 100644
--- a/matlab/dynare.m
+++ b/matlab/dynare.m
@@ -34,11 +34,11 @@ function dynare(fname, varargin)
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if strcmpi(fname,'help')
- disp(' ')
+ skipline()
disp(['This is dynare version ' dynare_version() '.'])
- disp(' ')
+ skipline()
disp('USAGE: dynare FILENAME[.mod,.dyn] [OPTIONS]')
- disp(' ')
+ skipline()
disp('dynare executes instruction included in FILENAME.mod.')
disp('See the reference manual for the available options.')
return
diff --git a/matlab/dynare_config.m b/matlab/dynare_config.m
index 473b9e1fa8d49f75eb8ee8eb54429ea9977f5a37..2cd7b74878da842c131de3ab6cdd91243c7d1729 100644
--- a/matlab/dynare_config.m
+++ b/matlab/dynare_config.m
@@ -220,7 +220,7 @@ end
%% Test if valid mex files are available, if a mex file is not available
%% a matlab version of the routine is included in the path.
if verbose
- disp(' ')
+ skipline()
disp('Configuring Dynare ...')
end
@@ -285,7 +285,7 @@ else
end
if verbose
disp([ message 'Markov Switching SBVAR.' ])
- disp(' ')
+ skipline()
end
cd(origin);
diff --git a/matlab/dynare_estimation_init.m b/matlab/dynare_estimation_init.m
index e99b73bb6a593052a8420b65a8d6b5af9c9639ad..9626306e77298d7975094eae2db2ff5dde80130c 100644
--- a/matlab/dynare_estimation_init.m
+++ b/matlab/dynare_estimation_init.m
@@ -53,7 +53,7 @@ for i = 1:size(M_.endo_names,1)
tmp = strmatch(deblank(M_.endo_names(i,:)),options_.varobs,'exact');
if ~isempty(tmp)
if length(tmp)>1
- disp(' ')
+ skipline()
error(['Multiple declarations of ' deblank(M_.endo_names(i,:)) ' as an observed variable is not allowed!'])
end
options_.lgyidx2varobs(i) = tmp;
diff --git a/matlab/dynare_identification.m b/matlab/dynare_identification.m
index 47d6133fa3360e186fa3a3daee76ef9926f7460b..0f22ad9e21e3730109134000b89f41b6a90521f3 100644
--- a/matlab/dynare_identification.m
+++ b/matlab/dynare_identification.m
@@ -213,9 +213,9 @@ options_ident.max_dim_cova_group = min([options_ident.max_dim_cova_group,nparam-
MaxNumberOfBytes=options_.MaxNumberOfBytes;
store_options_ident = options_ident;
-disp(' ')
+skipline()
disp(['==== Identification analysis ====' ]),
-disp(' ')
+skipline()
if iload <=0,
@@ -272,11 +272,11 @@ if iload <=0,
[idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point, info] = ...
identification_analysis(params,indx,indexo,options_ident,dataset_, prior_exist, name_tex,1);
if info(1)~=0,
- disp(' ')
+ skipline()
disp('----------- ')
disp('Parameter error:')
disp(['The model does not solve for ', parameters, ' with error code info = ', int2str(info(1))]),
- disp(' ')
+ skipline()
if info(1)==1,
disp('info==1 %! The model doesn''t determine the current variables uniquely.')
elseif info(1)==2,
@@ -305,7 +305,7 @@ if iload <=0,
disp('info==30 %! Ergodic variance can''t be computed. ')
end
disp('----------- ')
- disp(' ')
+ skipline()
if any(bayestopt_.pshape)
disp('Try sampling up to 50 parameter sets from the prior.')
kk=0;
@@ -317,15 +317,15 @@ if iload <=0,
end
end
if info(1)
- disp(' ')
+ skipline()
disp('----------- ')
disp('Identification stopped:')
if any(bayestopt_.pshape)
disp('The model did not solve for any of 50 attempts of random samples from the prior')
end
disp('----------- ')
- disp(' ')
- return,
+ skipline()
+ return
end
else
idehess_point.params=params;
@@ -343,7 +343,7 @@ if iload <=0,
end
if SampleSize > 1,
- disp(' ')
+ skipline()
disp('Monte Carlo Testing')
h = dyn_waitbar(0,'Monte Carlo identification checks ...');
iteration = 0;
@@ -587,7 +587,6 @@ else
warning on,
end
-disp(' ')
+skipline()
disp(['==== Identification analysis completed ====' ]),
-disp(' ')
-disp(' ')
+skipline(2)
diff --git a/matlab/dynare_sensitivity.m b/matlab/dynare_sensitivity.m
index 719cbf02b8c4e09500bf796a0d5d4ea7d81f2ede..14df1e83beeea16d1904d9226938e1fcb2f14efd 100644
--- a/matlab/dynare_sensitivity.m
+++ b/matlab/dynare_sensitivity.m
@@ -215,7 +215,7 @@ if (options_gsa.load_stab || options_gsa.load_rmse || options_gsa.load_redform)
any(bayestopt_.p4(~isnan(bayestopt_.p4))~=bkpprior.p4(~isnan(bkpprior.p4))),
disp('WARNING!')
disp('The saved sample has different priors w.r.t. to current ones!!')
- disp('')
+ skipline()
disp('Press ENTER to continue')
pause;
end
@@ -226,7 +226,7 @@ end
if options_gsa.stab && ~options_gsa.ppost,
x0 = stab_map_(OutputDirectoryName,options_gsa);
if isempty(x0),
- disp(' ')
+ skipline()
disp('Sensitivity computations stopped: no parameter set provided a unique solution')
return
end
diff --git a/matlab/evaluate_planner_objective.m b/matlab/evaluate_planner_objective.m
index e0a7fb7475676f96717da51bc718a82c00137c86..3067414af2e8c206f46688a56d7f4e2bb4f461e4 100644
--- a/matlab/evaluate_planner_objective.m
+++ b/matlab/evaluate_planner_objective.m
@@ -137,11 +137,11 @@ if options.ramsey_policy
end
if ~options.noprint
- disp(' ')
+ skipline()
disp('Approximated value of planner objective function')
disp([' - with initial Lagrange multipliers set to 0: ' ...
num2str(planner_objective_value(2)) ])
disp([' - with initial Lagrange multipliers set to steady state: ' ...
num2str(planner_objective_value(1)) ])
- disp(' ')
+ skipline()
end
diff --git a/matlab/forcst_unc.m b/matlab/forcst_unc.m
index a402837da9cebac1f25bc66501649ea979e9a3d7..139b09f915402fd67270c3d5f7c744af1e04bed0 100644
--- a/matlab/forcst_unc.m
+++ b/matlab/forcst_unc.m
@@ -91,13 +91,11 @@ end
oo_.forecast.accept_rate = (replic-m1)/replic;
if options_.noprint == 0 && m1 < replic
- disp(' ')
- disp(' ')
+ skipline(2)
disp('FORECASTING WITH PARAMETER UNCERTAINTY:')
disp(sprintf(['The model couldn''t be solved for %f%% of the parameter' ...
' values'],100*oo_.forecast.accept_rate))
- disp(' ')
- disp(' ')
+ skipline(2)
end
% compute moments
diff --git a/matlab/get_prior_info.m b/matlab/get_prior_info.m
index c8bd8fdddb384cd97da93f8c8085884bd1bdcc47..cbae72ed13914f4be1ce885947b706200c0d8674 100644
--- a/matlab/get_prior_info.m
+++ b/matlab/get_prior_info.m
@@ -167,18 +167,17 @@ if info==2% Prior optimization.
bayestopt_.p3, ...
bayestopt_.p4,options_,M_,estim_params_,oo_);
% Display the results.
- disp(' ')
- disp(' ')
+ skipline(2)
disp('------------------')
disp('PRIOR OPTIMIZATION')
disp('------------------')
- disp(' ')
+ skipline()
for i = 1:length(xparams)
disp(['deep parameter ' int2str(i) ': ' get_the_name(i,0,M_,estim_params_,options_) '.'])
disp([' Initial condition ....... ' num2str(xinit(i)) '.'])
disp([' Prior mode .............. ' num2str(bayestopt_.p5(i)) '.'])
disp([' Optimized prior mode .... ' num2str(xparams(i)) '.'])
- disp(' ')
+ skipline()
end
end
diff --git a/matlab/gsa/Morris_Measure_Groups.m b/matlab/gsa/Morris_Measure_Groups.m
index a807b808575a62e05d022e6deb03af8cf0c8129b..5b6c30720b8fb6871133093167dc073885f10735 100644
--- a/matlab/gsa/Morris_Measure_Groups.m
+++ b/matlab/gsa/Morris_Measure_Groups.m
@@ -40,7 +40,7 @@ function [SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p,
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if nargin==0,
- disp(' ')
+ skipline()
disp('[SAmeas, OutMatrix] = Morris_Measure_Groups(NumFact, Sample, Output, p, Group);')
return
end
diff --git a/matlab/gsa/filt_mc_.m b/matlab/gsa/filt_mc_.m
index 5ced8be595376fe61e79a5b9a5ee2ed7fe92485f..53bf376db8ffb5caa2d1b871acaf0922dbf05098 100644
--- a/matlab/gsa/filt_mc_.m
+++ b/matlab/gsa/filt_mc_.m
@@ -50,11 +50,10 @@ fname_ = M_.fname;
lgy_ = M_.endo_names;
dr_ = oo_.dr;
-disp(' ')
-disp(' ')
+skipline(2)
disp('Starting sensitivity analysis')
disp('for the fit of EACH observed series ...')
-disp(' ')
+skipline()
disp('Deleting old SA figures...')
a=dir([OutDir,filesep,'*.*']);
tmp1='0';
@@ -149,7 +148,7 @@ if ~loadSA,
nruns=size(x,1);
nfilt=floor(pfilt*nruns);
if options_.opt_gsa.ppost || (options_.opt_gsa.ppost==0 && options_.opt_gsa.lik_only==0)
- disp(' ')
+ skipline()
disp('Computing RMSE''s...')
fobs = options_.first_obs;
nobs=options_.nobs;
@@ -408,7 +407,7 @@ else
end
param_names=param_names(2:end,:);
- disp(' ')
+ skipline()
disp('RMSE over the MC sample:')
disp(' min yr RMSE max yr RMSE')
for j=1:size(vvarvecm,1),
@@ -416,8 +415,7 @@ else
end
invar = find( std(rmse_MC)./mean(rmse_MC)<=0.0001 );
if ~isempty(invar)
- disp(' ')
- disp(' ')
+ skipline(2)
disp('RMSE is not varying significantly over the MC sample for the following variables:')
disp(vvarvecm(invar,:))
disp('These variables are excluded from SA')
@@ -427,7 +425,7 @@ else
vvarvecm=vvarvecm(ivar,:);
rmse_MC=rmse_MC(:,ivar);
- disp(' ')
+ skipline()
% if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
disp(['Sample filtered the ',num2str(pfilt*100),'% best RMSE''s for each observed series ...' ])
% else
@@ -437,8 +435,7 @@ else
% set(gca,'xticklabel',vvarvecm)
% saveas(gcf,[fname_,'_SA_RMSE'])
- disp(' ')
- disp(' ')
+ skipline(2)
disp('RMSE ranges after filtering:')
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
disp([' best ',num2str(pfilt*100),'% filtered remaining 90%'])
@@ -461,7 +458,7 @@ else
%%%%% R2 table
- disp(' ')
+ skipline()
disp('R2 over the MC sample:')
disp(' min yr R2 max yr R2')
for j=1:size(vvarvecm,1),
@@ -469,11 +466,10 @@ else
end
r2_MC=r2_MC(:,ivar);
- disp(' ')
+ skipline()
disp(['Sample filtered the ',num2str(pfilt*100),'% best R2''s for each observed series ...' ])
- disp(' ')
- disp(' ')
+ skipline()
disp('R2 ranges after filtering:')
if options_.opt_gsa.ppost==0 && options_.opt_gsa.pprior,
disp([' best ',num2str(pfilt*100),'% filtered remaining 90%'])
@@ -511,14 +507,13 @@ else
% snam=bayestopt_.name(find(nsp>0));
nsnam=(find(nsp>1));
- disp(' ')
- disp(' ')
+ skipline(2
disp('These parameters do not affect significantly the fit of ANY observed series:')
disp(snam0)
- disp(' ')
+ skipline()
disp('These parameters affect ONE single observed series:')
disp(snam1)
- disp(' ')
+ skipline()
disp('These parameters affect MORE THAN ONE observed series: trade off exists!')
disp(snam2)
@@ -594,8 +589,7 @@ else
nsx(j)=length(find(SP(:,j)));
end
- disp(' ')
- disp(' ')
+ skipline(2
disp('Sensitivity table (significance and direction):')
vav=char(zeros(1, size(param_names,2)+3 ));
ibl = 12-size(vvarvecm,2);
@@ -610,8 +604,7 @@ else
end
- disp(' ')
- disp(' ')
+ skipline()
disp('Starting bivariate analysis:')
for i=1:size(vvarvecm,1)
diff --git a/matlab/gsa/gsa_speed.m b/matlab/gsa/gsa_speed.m
index bd335841023c51be8384f942b19ceba40a65fffc..d0845c57f8b3de6ed76ab9b7d03cfe6969f05911 100644
--- a/matlab/gsa/gsa_speed.m
+++ b/matlab/gsa/gsa_speed.m
@@ -56,6 +56,6 @@ for i=1:nrun,
end
dyn_waitbar(i/nrun,h)
end
-disp(' ')
+skipline()
disp('.. done !')
dyn_waitbar_close(h)
diff --git a/matlab/gsa/mc_moments.m b/matlab/gsa/mc_moments.m
index 22838d9ce83cc1c19133792a18c8cfa13f019498..31fd3bce65f95430f56311effb176b42f849ce21 100644
--- a/matlab/gsa/mc_moments.m
+++ b/matlab/gsa/mc_moments.m
@@ -39,5 +39,5 @@ global options_ M_
dyn_waitbar(j/nsam,h)
end
dyn_waitbar_close(h)
- disp(' ')
+ skipline()
disp('... done !')
diff --git a/matlab/gsa/redform_map.m b/matlab/gsa/redform_map.m
index eb6c8e0cf5e594456740f2d1fe2f655fa60c0bdd..94c56a41dd54c98f0bc01081f4f74acfc030591f 100644
--- a/matlab/gsa/redform_map.m
+++ b/matlab/gsa/redform_map.m
@@ -116,7 +116,7 @@ for j=1:size(anamendo,1)
for jx=1:size(anamexo,1)
namexo=deblank(anamexo(jx,:));
iexo=strmatch(namexo,M_.exo_names,'exact');
- disp(' ')
+ skipline()
disp(['[', namendo,' vs. ',namexo,']'])
@@ -162,7 +162,7 @@ for j=1:size(anamendo,1)
for jp=1:length(indsmirnov),
disp([M_.param_names(estim_params_.param_vals(indsmirnov(jp),1),:),' d-stat = ', num2str(dproba(indsmirnov(jp)),'%1.3f'),' p-value = ', num2str(proba(indsmirnov(jp)),'%1.3f')])
end
- disp(' ');
+ skipline()
stab_map_1(x0, iy, iyc, 'threshold',pvalue_ks,indsmirnov,xdir,[],['Reduced Form Mapping (Threshold) for ', namendo,' vs. lagged ', namexo]);
stab_map_2(x0(iy,:),alpha2,pvalue_corr,'inside_threshold',xdir,[],['Reduced Form Mapping (Inside Threshold)for ', namendo,' vs. lagged ', namexo])
stab_map_2(x0(iyc,:),alpha2,pvalue_corr,'outside_threshold',xdir,[],['Reduced Form Mapping (Outside Threshold) for ', namendo,' vs. lagged ', namexo])
@@ -218,7 +218,7 @@ for j=1:size(anamendo,1)
for je=1:size(anamlagendo,1)
namlagendo=deblank(anamlagendo(je,:));
ilagendo=strmatch(namlagendo,M_.endo_names(oo_.dr.order_var(M_.nstatic+1:M_.nstatic+nsok),:),'exact');
- disp(' ')
+ skipline()
disp(['[', namendo,' vs. lagged ',namlagendo,']'])
if ~isempty(ilagendo),
@@ -261,7 +261,7 @@ for j=1:size(anamendo,1)
for jp=1:length(indsmirnov),
disp([M_.param_names(estim_params_.param_vals(indsmirnov(jp),1),:),' d-stat = ', num2str(dproba(indsmirnov(jp)),'%1.3f'),' p-value = ', num2str(proba(indsmirnov(jp)),'%1.3f')])
end
- disp(' ');
+ skipline()
stab_map_1(x0, iy, iyc, 'threshold',pvalue_ks,indsmirnov,xdir,[],['Reduced Form Mapping (Threshold) for ', namendo,' vs. lagged ', namlagendo]);
stab_map_2(x0(iy,:),alpha2,pvalue_corr,'inside_threshold',xdir,[],['Reduced Form Mapping (Inside Threshold) for ', namendo,' vs. lagged ', namlagendo])
stab_map_2(x0(iyc,:),alpha2,pvalue_corr,'outside_threshold',xdir,[],['Reduced Form Mapping (Outside Threshold) for ', namendo,' vs. lagged ', namlagendo])
diff --git a/matlab/gsa/stab_map_.m b/matlab/gsa/stab_map_.m
index de220c3c89464a4154277d58618180f4816c67dc..ca8a54f7fd402529c6114d6b6dceb6a9b35b3c8c 100644
--- a/matlab/gsa/stab_map_.m
+++ b/matlab/gsa/stab_map_.m
@@ -499,9 +499,9 @@ if length(iunstable)>0 && length(iunstable)<Nsam,
fprintf(['%4.1f%% of the prior support gives indeterminacy.'],length(iindeterm)/Nsam*100)
end
if ~isempty(iwrong),
- disp(' ');
+ skipline()
disp(['For ',num2str(length(iwrong)/Nsam*100,'%1.3f'),'\% of the prior support dynare could not find a solution.'])
- disp(' ');
+ skipline()
if any(infox==1),
disp([' For ',num2str(length(find(infox==1))/Nsam*100,'%1.3f'),'\% The model doesn''t determine the current variables uniquely.'])
end
@@ -534,7 +534,7 @@ if length(iunstable)>0 && length(iunstable)<Nsam,
end
end
- disp(' ');
+ skipline()
% Blanchard Kahn
[proba, dproba] = stab_map_1(lpmat, istable, iunstable, aname,0);
% indstab=find(dproba>ksstat);
@@ -543,7 +543,7 @@ if length(iunstable)>0 && length(iunstable)<Nsam,
for j=1:length(indstab),
disp([M_.param_names(estim_params_.param_vals(indstab(j),1),:),' d-stat = ', num2str(dproba(indstab(j)),'%1.3f'),' p-value = ', num2str(proba(indstab(j)),'%1.3f')])
end
- disp(' ');
+ skipline()
if ~isempty(indstab)
stab_map_1(lpmat, istable, iunstable, aname, 1, indstab, OutputDirectoryName,[],atitle);
end
@@ -556,7 +556,7 @@ if length(iunstable)>0 && length(iunstable)<Nsam,
for j=1:length(indindet),
disp([M_.param_names(estim_params_.param_vals(indindet(j),1),:),' d-stat = ', num2str(dproba(indindet(j)),'%1.3f'),' p-value = ', num2str(proba(indindet(j)),'%1.3f')])
end
- disp(' ');
+ skipline()
if ~isempty(indindet)
stab_map_1(lpmat, [1:Nsam], iindeterm, aindetname, 1, indindet, OutputDirectoryName,[],aindettitle);
end
@@ -570,7 +570,7 @@ if length(iunstable)>0 && length(iunstable)<Nsam,
for j=1:length(indunst),
disp([M_.param_names(estim_params_.param_vals(indunst(j),1),:),' d-stat = ', num2str(dproba(indunst(j)),'%1.3f'),' p-value = ', num2str(proba(indunst(j)),'%1.3f')])
end
- disp(' ');
+ skipline()
if ~isempty(indunst)
stab_map_1(lpmat, [1:Nsam], ixun, aunstablename, 1, indunst, OutputDirectoryName,[],aunstabletitle);
end
@@ -584,13 +584,13 @@ if length(iunstable)>0 && length(iunstable)<Nsam,
for j=1:length(indwrong),
disp([M_.param_names(estim_params_.param_vals(indwrong(j),1),:),' d-stat = ', num2str(dproba(indwrong(j)),'%1.3f'),' p-value = ', num2str(proba(indwrong(j)),'%1.3f')])
end
- disp(' ');
+ skipline()
if ~isempty(indwrong)
stab_map_1(lpmat, [1:Nsam], iwrong, awronguniname, 1, indwrong, OutputDirectoryName,[],awrongunititle);
end
end
- disp(' ')
+ skipline()
disp('Starting bivariate analysis:')
c0=corrcoef(lpmat(istable,:));
diff --git a/matlab/independent_metropolis_hastings.m b/matlab/independent_metropolis_hastings.m
index afbe037013a1c027d3de7e6ae521a15697e5e3d9..577c4000566c609e5dfc1e74b93156d74eb45f74 100644
--- a/matlab/independent_metropolis_hastings.m
+++ b/matlab/independent_metropolis_hastings.m
@@ -122,4 +122,4 @@ disp(['MH: Total number of generated files : ' int2str(NewFile(1)*nblck) '.
disp(['MH: Total number of iterations : ' int2str((NewFile(1)-1)*MAX_nruns+irun-1) '.'])
disp('MH: average acceptation rate per chain : ')
disp(record.AcceptationRates);
-disp(' ')
\ No newline at end of file
+skipline()
\ No newline at end of file
diff --git a/matlab/independent_metropolis_hastings_core.m b/matlab/independent_metropolis_hastings_core.m
index e6c8c3f5e6d1eb9a068ddf2946899c22ed477125..3162bd402ea6d2fa057fc32ad80a3cdbe0a8677f 100644
--- a/matlab/independent_metropolis_hastings_core.m
+++ b/matlab/independent_metropolis_hastings_core.m
@@ -130,7 +130,7 @@ for b = fblck:nblck,
end
if exist('OCTAVE_VERSION') || options_.console_mode
diary off
- disp(' ')
+ skipline()
elseif whoiam
% keyboard;
waitbarString = ['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...'];
diff --git a/matlab/marginal_density.m b/matlab/marginal_density.m
index 40170def9fcee0af718fdca9f04bac765cb7db88..5b30f8298e8e166b3b9211ccc59e298e4d297815 100644
--- a/matlab/marginal_density.m
+++ b/matlab/marginal_density.m
@@ -60,8 +60,7 @@ fprintf(' Done!\n');
%% (usefull if the user wants to perform some computations using
%% the posterior mean instead of the posterior mode ==> ).
save([M_.fname '_mean.mat'],'xparam1','hh','SIGMA');
-
-disp(' ');
+skipline()
disp('MH: I''m computing the posterior log marginal density (modified harmonic mean)... ');
detSIGMA = det(SIGMA);
invSIGMA = inv(SIGMA);
diff --git a/matlab/metropolis_hastings_initialization.m b/matlab/metropolis_hastings_initialization.m
index e42407b24ce85f27fc9d5090478956918df36bba..b90f72130961a4d43f49edd96d22ef644f81634f 100644
--- a/matlab/metropolis_hastings_initialization.m
+++ b/matlab/metropolis_hastings_initialization.m
@@ -146,7 +146,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
end
fprintf(fidlog,' \n');
disp('MH: Initial values found!')
- disp(' ')
+ skipline()
else% Case 2: one chain (we start from the posterior mode)
fprintf(fidlog,[' Initial values of the parameters:\n']);
candidate = transpose(xparam1(:));%
@@ -154,7 +154,7 @@ if ~options_.load_mh_file && ~options_.mh_recover
ix2 = candidate;
ilogpo2 = - feval(TargetFun,ix2',dataset_,options_,M_,estim_params_,bayestopt_,oo_);
disp('MH: Initialization at the posterior mode.')
- disp(' ')
+ skipline()
fprintf(fidlog,[' Blck ' int2str(1) 'params:\n']);
for i=1:length(ix2(1,:))
fprintf(fidlog,[' ' int2str(i) ':' num2str(ix2(1,i)) '\n']);
@@ -276,13 +276,13 @@ elseif options_.load_mh_file && ~options_.mh_recover
record.MhDraws(end,3) = AnticipatedNumberOfLinesInTheLastFile;
save([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
disp(['MH: ... It''s done. I''ve loaded ' int2str(NumberOfPreviousSimulations) ' simulations.'])
- disp(' ')
+ skipline()
fclose(fidlog);
elseif options_.mh_recover
%% The previous metropolis-hastings crashed before the end! I try to
%% recover the saved draws...
disp('MH: Recover mode!')
- disp(' ')
+ skipline()
file = dir([MhDirectoryName '/' ModelName '_mh_history.mat']);
if ~length(file)
error('MH:: FAILURE! there is no MH-history file!')
diff --git a/matlab/mode_check.m b/matlab/mode_check.m
index 6f9299ac1435f5689c0b7959fbc3d28619954ffa..e7591e21dff3666def7628e8d7b8a5c62bcaf75a 100644
--- a/matlab/mode_check.m
+++ b/matlab/mode_check.m
@@ -65,11 +65,11 @@ end
fval = feval(fun,x,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
if ~isempty(hessian);
- disp(' ')
+ skipline()
disp('MODE CHECK')
- disp(' ')
+ skipline()
disp(sprintf('Fval obtained by the minimization routine: %f', fval))
- disp(' ')
+ skipline()
if s_min<eps
disp(sprintf('Most negative variance %f for parameter %d (%s = %f)', s_min, k , BayesInfo.name{k}, x(k)))
end
diff --git a/matlab/model_comparison.m b/matlab/model_comparison.m
index d5065aa9ddf3b2ffa5b310372d4638b36af519c0..0ff60e45396c6fd760d9cb6c507256fc9961ba69 100644
--- a/matlab/model_comparison.m
+++ b/matlab/model_comparison.m
@@ -31,8 +31,7 @@ function PosteriorOddsTable = model_comparison(ModelNames,ModelPriors,oo,options
NumberOfModels = size(ModelNames,2);
-disp(' ')
-disp(' ')
+skipline(2)
if isempty(ModelPriors)
prior_flag = 0;% empty_prior=0
ModelPriors = ones(NumberOfModels,1)/NumberOfModels;
diff --git a/matlab/ms-sbvar/ms_mardd.m b/matlab/ms-sbvar/ms_mardd.m
index 7b83b2453578f11d46fe4b385f7d25af1c5a1b59..9932f0186a38c5bd44decd28eced194f31b666cd 100644
--- a/matlab/ms-sbvar/ms_mardd.m
+++ b/matlab/ms-sbvar/ms_mardd.m
@@ -129,7 +129,7 @@ for k=1:nvar
%--------- The 1st set of draws to be tossed away. ------------------
for draws = 1:ndraws1
if ~mod(draws,nbuffer)
- disp(' ')
+ skipline()
disp(sprintf('The %dth column or equation in A0 with %d 1st tossed-away draws in Gibbs',k,draws))
end
A0gbs1 = fn_gibbsrvar(A0gbs0,UT,nvar,fss,n0,indx_ks);
@@ -140,7 +140,7 @@ for k=1:nvar
%--------- The 2nd set of draws to be used. ------------------
for draws = 1:ndraws2
if ~mod(draws,nbuffer)
- disp(' ')
+ skipline()
disp(sprintf('The %dth column or equation in A0 with %d usable draws in Gibbs',k,draws))
end
[A0gbs1, Wcell] = fn_gibbsrvar(A0gbs0,UT,nvar,fss,n0,indx_ks);
@@ -162,7 +162,7 @@ for k=1:nvar
vlog_a0_Yao(k) = vlogxhat;
% The log value of p(a0_k|Y,a_others) where a_others: other a's at some point such as the peak of ONLY some a0's
else
- disp(' ')
+ skipline()
disp(sprintf('The last(6th) column or equation in A0 with no Gibbs draws'))
[A0gbs1, Wcell] = fn_gibbsrvar(A0gbs0,UT,nvar,fss,n0,indx_ks)
%------ See p.71, Forecast (II).
@@ -191,7 +191,6 @@ disp('Posterior pdf -- log(p(aphat|a0hat, Y)):');
vlog_ap_Ya0
%--------- The value of marginal density p(Y) ----------
-disp(' ');
-disp(' ');
+skipline()
disp('************ Marginal Likelihood of Y or Marginal Data Density: ************');
vlogY = vlog_a0p+vlog_Y_a-sum(vlog_a0_Yao)-vlog_ap_Ya0
diff --git a/matlab/ms-sbvar/msstart2.m b/matlab/ms-sbvar/msstart2.m
index 2c1ae25242c5e69d859f75e7ae8a36260036a188..6fa5861cd9cb981536c1fc0b21b0ca00d0f0e21c 100644
--- a/matlab/ms-sbvar/msstart2.m
+++ b/matlab/ms-sbvar/msstart2.m
@@ -154,7 +154,7 @@ if cnum
end
%
pause(1)
-disp(' ')
+skipline()
disp('For uncondtional forecasts, set nconstr = options_.ms.cms = cnum = 0')
pause(1)
%
@@ -296,12 +296,12 @@ if options_.ms.indxestima
%* Obtain linear restrictions
[Uiconst,Viconst,n0,np,ixmC0Pres] = feval(options_.ms.restriction_fname,nvar,nexo,options_.ms );
if min(n0)==0
- disp(' ')
+ skipline()
warning('A0: restrictions in dlrprior.m give no free parameter in one of equations')
disp('Press ctrl-c to abort')
pause
elseif min(np)==0
- disp(' ')
+ skipline()
warning('Ap: Restrictions in dlrprior.m give no free parameter in one of equations')
disp('Press ctrl-c to abort')
pause
diff --git a/matlab/ms-sbvar/msstart_setup.m b/matlab/ms-sbvar/msstart_setup.m
index 4456cd11752368f3e6c594cc05f40f6fd056a1ed..2d322211d84a5dad7928a2c5d2b465c90c73b50d 100644
--- a/matlab/ms-sbvar/msstart_setup.m
+++ b/matlab/ms-sbvar/msstart_setup.m
@@ -61,7 +61,7 @@ nvar = size(options_.varobs,1); % number of endogenous variables
nlogeno = length(options_.ms.log_var); % number of endogenous variables in options_.ms.log_var
npereno = length(options_.ms.percent_var); % number of endogenous variables in options_.ms.percent_var
if (nvar~=(nlogeno+npereno))
- disp(' ')
+ skipline()
warning('Check xlab, nlogeno or npereno to make sure of endogenous variables in options_.ms.vlist')
disp('Press ctrl-c to abort')
return
@@ -70,7 +70,7 @@ elseif (nvar==length(options_.ms.vlist))
elseif (nvar<length(options_.ms.vlist))
nexo=length(options_.ms.vlist)-nvar+1;
else
- disp(' ')
+ skipline()
warning('Make sure there are only nvar endogenous variables in options_.ms.vlist')
disp('Press ctrl-c to abort')
return
diff --git a/matlab/mult_elimination.m b/matlab/mult_elimination.m
index eed37d771bc85d368d8ac26c4c39c26a1372e5ba..ec3ef5cbb152a591607afc1afb1b5b9a39e74b27 100644
--- a/matlab/mult_elimination.m
+++ b/matlab/mult_elimination.m
@@ -129,5 +129,5 @@ if nvar > 0 && options_.noprint == 0
end
lh = size(labels,2)+2;
dyntable(my_title,headers,labels,res_table,lh,10,6);
- disp(' ')
+ skipline()
end
diff --git a/matlab/newrat.m b/matlab/newrat.m
index 3ce1dbd10fec35aa0061295b37dfbfc87d529324..5b2c7e7d9ecc51cc7c4a4d71ac8ef4395ed13c2f 100644
--- a/matlab/newrat.m
+++ b/matlab/newrat.m
@@ -214,10 +214,10 @@ while norm(gg)>gtol && check==0 && jit<nit
end
if htol0>htol
htol=htol0;
- disp(' ')
+ skipline()
disp('Numerical noise in the likelihood')
disp('Tolerance has to be relaxed')
- disp(' ')
+ skipline()
end
if ~outer_product_gradient,
H = bfgsi1(H,gg-g(:,icount),xparam1-x(:,icount));
@@ -256,16 +256,16 @@ end
save m1.mat x hh g hhg igg fval0 nig
if ftol>ftol0
- disp(' ')
+ skipline()
disp('Numerical noise in the likelihood')
disp('Tolerance had to be relaxed')
- disp(' ')
+ skipline()
end
if jit==nit
- disp(' ')
+ skipline()
disp('Maximum number of iterations reached')
- disp(' ')
+ skipline()
end
if norm(gg)<=gtol
diff --git a/matlab/osr.m b/matlab/osr.m
index ccb7c0c7d8b56782c47d83fed3be104a3a3df52f..325ab943b78525e14106361b1d7cb48cf8b00e1d 100644
--- a/matlab/osr.m
+++ b/matlab/osr.m
@@ -34,9 +34,9 @@ for i=1:np
i_params(i) = strmatch(deblank(params(i,:)),M_.param_names,'exact');
end
-disp(' ')
+skipline()
disp('OPTIMAL SIMPLE RULE')
-disp(' ')
+skipline()
osr1(i_params,i_var,W);
stoch_simul(var_list);
\ No newline at end of file
diff --git a/matlab/osr1.m b/matlab/osr1.m
index 601355f7c0e3cabf9555c913cba63a9a0ce26b81..7709368d14105c0f9c24fd0e9ad357a9809160cc 100644
--- a/matlab/osr1.m
+++ b/matlab/osr1.m
@@ -63,14 +63,14 @@ oo_.osr.objective_function = f;
-disp('')
+skipline()
disp('OPTIMAL VALUE OF THE PARAMETERS:')
-disp('')
+skipline()
for i=1:np
disp(sprintf('%16s %16.6g\n',M_.param_names(i_params(i),:),p(i)))
end
disp(sprintf('Objective function : %16.6g\n',f));
-disp(' ')
+skipline()
[oo_.dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
% 05/10/03 MJ modified to work with osr.m and give full report
\ No newline at end of file
diff --git a/matlab/parallel/AnalyseComputationalEnvironment.m b/matlab/parallel/AnalyseComputationalEnvironment.m
index 6d5d074303ad90aff4104697bdde789bfa2e479a..f6dd9e970a436fffac5c5ca5241b6c0310a98bea 100644
--- a/matlab/parallel/AnalyseComputationalEnvironment.m
+++ b/matlab/parallel/AnalyseComputationalEnvironment.m
@@ -123,11 +123,9 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
Environment= (OScallerUnix || OStargetUnix);
- disp(' ');
- disp(' ');
+ skipline(2)
disp(['Testing computer -> ',DataInput(Node).ComputerName,' <- ...']);
- disp(' ');
- disp(' ');
+ skipline(2)
% The function is composed by two main blocks, determined by the 'Local'
% variable.
@@ -138,18 +136,14 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
if ((DataInput(Node).Local == 0) |(DataInput(Node).Local == 1))
% Continue it is Ok!
disp('Check on Local Variable ..... Ok!');
- disp(' ');
- disp(' ');
-
+ skipline()
else
disp('The variable "Local" has a bad value!');
- disp(' ');
+ skipline()
disp('ErrorCode 1.');
- disp(' ');
- disp(' ');
+ skipline()
ErrorCode=1;
return
-
end
% %%%%%%%%%% Local (No Network) Computing %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -189,17 +183,14 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
end
if (si1)
- disp(['It is impossibile to ping to the computer with name "',DataInput(Node).ComputerName,'" using the network!']);
- disp(' ');
- disp('ErrorCode 3.');
+ disp(['It is impossibile to ping to the computer with name "',DataInput(Node).ComputerName,'" using the network!'])
+ skipline()
+ disp('ErrorCode 3.')
ErrorCode=3;
- disp(' ');
- disp(' ');
-% return;
+ skipline(2)
else
- disp('Check on ComputerName Variable ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on ComputerName Variable ..... Ok!')
+ skipline(2)
end
@@ -212,34 +203,29 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
% strategy.
if (isempty(DataInput(Node).UserName))
- disp('The fields UserName is empty!');
- disp(' ');
- disp('ErrorCode 4.');
- disp(' ');
- disp(' ');
+ disp('The fields UserName is empty!')
+ skipline()
+ disp('ErrorCode 4.')
+ skipline(2)
ErrorCode=4;
return
end
- disp('Check on UserName Variable ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on UserName Variable ..... Ok!')
+ skipline(2)
% This check can be removed ... according to the dynare parser
% strategy.
if (~isempty(DataInput(Node).Password))
disp('[WARNING] The field Password should be empty under unix or mac!');
- disp(' ');
- disp(['Remove the string ',DataInput(Node).Password,' from this field!']);
- disp(' ');
- disp('ErrorCode 4.');
- disp(' ');
- disp(' ');
+ skipline()
+ disp(['Remove the string ',DataInput(Node).Password,' from this field!'])
+ skipline()
+ disp('ErrorCode 4.')
+ skipline(2)
ErrorCode=4;
- % return
else
- disp('Check on Password Variable ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on Password Variable ..... Ok!')
+ skipline(2)
end
else
@@ -248,20 +234,16 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
if (isempty(DataInput(Node).UserName)) || (isempty(DataInput(Node).Password))
disp('The fields UserName and/or Password are/is empty!');
- disp(' ');
- disp('ErrorCode 4.');
- disp(' ');
- disp(' ');
+ skipline()
+ disp('ErrorCode 4.')
+ skipline(2)
ErrorCode=4;
return
end
disp('Check on UserName Variable ..... Ok!');
- disp(' ');
- disp(' ');
+ skipline()
disp('Check on Password Variable ..... Ok!');
- disp(' ');
- disp(' ');
-
+ skipline()
end
% Now we very if RemoteDrive and/or RemoteDirectory exist on remote
@@ -273,11 +255,10 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
% strategy.
if isempty(DataInput(Node).RemoteDirectory)
- disp('The field RemoteDirectory is empty!');
- disp(' ');
- disp('ErrorCode 5.');
- disp(' ');
- disp(' ');
+ disp('The field RemoteDirectory is empty!')
+ skipline()
+ disp('ErrorCode 5.')
+ skipline()
ErrorCode=5;
return
end
@@ -286,15 +267,13 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
% strategy.
if (~isempty(DataInput(Node).RemoteDrive))
- disp('[WARNING] The fields RemoteDrive should be empty under unix or mac!');
- disp(' ');
- disp(['remove the string ',DataInput(Node).RemoteDrive,' from this field!']);
- disp(' ');
- disp('ErrorCode 5.');
- disp(' ');
- disp(' ');
+ disp('[WARNING] The fields RemoteDrive should be empty under unix or mac!')
+ skipline()
+ disp(['remove the string ',DataInput(Node).RemoteDrive,' from this field!'])
+ skipline()
+ disp('ErrorCode 5.')
+ skipline(2)
ErrorCode=5;
- % return
end
si2=[];
@@ -308,32 +287,28 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
[si2 de2]=system(['ssh ',ssh_token,' ',DataInput(Node).UserName,'@',DataInput(Node).ComputerName,' ls ',DataInput(Node).RemoteDirectory,'/',RemoteTmpFolder,'/']);
if (si2)
- disp ('Remote Directory does not exist or is not reachable!');
- disp(' ');
- disp('ErrorCode 5.');
- disp(' ');
- disp(' ');
+ disp ('Remote Directory does not exist or is not reachable!')
+ skipline()
+ disp('ErrorCode 5.')
+ skipline(2)
ErrorCode=5;
return
end
- disp('Check on RemoteDirectory Variable ..... Ok!');
- disp(' ');
- disp(' ');
- disp('Check on RemoteDrive Variable ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on RemoteDirectory Variable ..... Ok!')
+ skipline(2)
+ disp('Check on RemoteDrive Variable ..... Ok!')
+ skipline(2)
else
% This check can be removed ... according to the dynare parser
% strategy.
if (isempty(DataInput(Node).RemoteDrive)||isempty(DataInput(Node).RemoteDirectory))
- disp('Remote RemoteDrive and/or RemoteDirectory is/are empty!');
- disp(' ');
- disp('ErrorCode 5.');
- disp(' ');
- disp(' ');
+ disp('Remote RemoteDrive and/or RemoteDirectory is/are empty!')
+ skipline()
+ disp('ErrorCode 5.')
+ skipline(2)
ErrorCode=5;
return
end
@@ -344,21 +319,18 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
[si2 de2]=system(['dir \\',DataInput(Node).ComputerName,'\',DataInput(Node).RemoteDrive,'$\',DataInput(Node).RemoteDirectory,'\',RemoteTmpFolder]);
if (si2)
- disp ('Remote Directory does not exist or it is not reachable!');
- disp(' ');
- disp('ErrorCode 5.');
- disp(' ');
- disp(' ');
+ disp ('Remote Directory does not exist or it is not reachable!')
+ skipline()
+ disp('ErrorCode 5.')
+ skipline(2)
ErrorCode=5;
return
end
- disp('Check on RemoteDirectory Variable ..... Ok!');
- disp(' ');
- disp(' ');
- disp('Check on RemoteDrive Variable ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on RemoteDirectory Variable ..... Ok!')
+ skipline(2)
+ disp('Check on RemoteDrive Variable ..... Ok!')
+ skipline(2)
end
@@ -407,17 +379,15 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
delete ('Tracing.m');
if (isempty(FindTracing))
- disp ('It is impossible to exchange data with Remote Drive and/or Remote Directory! ErrorCode 6.');
- disp(' ');
- disp('ErrorCode 6.');
- disp(' ');
- disp(' ');
+ disp('It is impossible to exchange data with Remote Drive and/or Remote Directory! ErrorCode 6.')
+ skipline()
+ disp('ErrorCode 6.')
+ skipline(2)
ErrorCode=6;
return
else
- disp('Check on Exchange File with Remote Computer ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on Exchange File with Remote Computer ..... Ok!')
+ skipline(2)
end
@@ -466,10 +436,10 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
while (1);
if Flag==0
- disp('Try to run matlab/octave on remote machine ... ');
- disp(' ');
- disp('please wait ... ');
- disp(' ');
+ disp('Try to run matlab/octave on remote machine ... ')
+ skipline()
+ disp('please wait ... ')
+ skipline()
Flag=1;
end
nt=fix(clock);
@@ -486,25 +456,22 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
if (ErrorCode==7)
- disp ('It is not possible execute a matlab session on remote machine!');
- disp(' ');
- disp('ErrorCode 7.');
- disp(' ');
- disp(' ');
+ disp ('It is not possible execute a matlab session on remote machine!')
+ skipline()
+ disp('ErrorCode 7.')
+ skipline(2)
ErrorCode=7;
dynareParallelRmDir(RemoteTmpFolder,DataInput(Node));
return
-
else
- disp('Check on MatlabOctave Path and MatlabOctave Program Execution on remote machine ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on MatlabOctave Path and MatlabOctave Program Execution on remote machine ..... Ok!')
+ skipline(2)
% Now we verify if the DynarePath is correct ...
- disp('Check the Dynare path on remote machine ... ');
- disp(' ');
- disp('please wait ... ');
- disp(' ');
+ disp('Check the Dynare path on remote machine ... ')
+ skipline()
+ disp('please wait ... ')
+ skipline(2)
pause(2)
if isempty(dynareParallelDir('DynareIsOk.txt',RemoteTmpFolder,DataInput(Node)))
@@ -512,20 +479,16 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
end
if (ErrorCode==8)
-
- disp ('The DynarePath is incorrect!');
- disp(' ');
- disp('ErrorCode 8.');
- disp(' ');
- disp(' ');
+ disp ('The DynarePath is incorrect!')
+ skipline()
+ disp('ErrorCode 8.')
+ skipline(2)
ErrorCode=8;
dynareParallelRmDir(RemoteTmpFolder,DataInput(Node));
return
-
else
- disp('Check on Dynare Path remote machine ..... Ok!');
- disp(' ');
- disp(' ');
+ disp('Check on Dynare Path remote machine ..... Ok!')
+ skipline(2)
end
end
@@ -539,15 +502,13 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
si3=dynareParallelDir('Tracing.m', RemoteTmpFolder,DataInput(Node));
if (isempty(si3))
- disp ('Check on Delete Remote Computational Traces ..... Ok!');
- disp(' ');
- disp(' ');
+ disp ('Check on Delete Remote Computational Traces ..... Ok!')
+ skipline(2)
else
- disp ('It is impossible to delete temporary files on remote machine!');
- disp(' ');
- disp('ErrorCode 9.');
- disp(' ');
- disp(' ');
+ disp ('It is impossible to delete temporary files on remote machine!')
+ skipline()
+ disp('ErrorCode 9.')
+ skipline(2)
ErrorCode=9;
return
end
@@ -563,11 +524,10 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
if yn==1
% The field is empty!
- disp('The field "CPUnbr" is empty!');
- disp(' ');
- disp('ErrorCode 2.');
- disp(' ');
- disp(' ');
+ disp('The field "CPUnbr" is empty!')
+ skipline()
+ disp('ErrorCode 2.')
+ skipline(2)
ErrorCode=2;
return
end
@@ -620,16 +580,16 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
if isempty (RealCPUnbr)
% An error occurred when we try to know the Cpu/Cores
% numbers.
- disp('It is impossible determine the number of Cpu/Processor avaiable on this machine!');
- disp(' ');
- disp('ErrorCode 2.');
- disp(' ');
+ disp('It is impossible determine the number of Cpu/Processor avaiable on this machine!')
+ skipline()
+ disp('ErrorCode 2.')
+ skipline()
if Environment
- disp('Check the command "$less /proc/cpuinfo" ... !');
+ disp('Check the command "$less /proc/cpuinfo" ... !')
else
- disp('Check if the pstools are installed and are in machine path! And check the command "psinfo \\"');
+ disp('Check if the pstools are installed and are in machine path! And check the command "psinfo \\"')
end
- disp(' ');
+ skipline()
ErrorCode=2;
return
end
@@ -642,38 +602,25 @@ for Node=1:length(DataInput) % To obtain a recoursive function remove the 'for'
CPUnbrUser=length(DataInput(Node).CPUnbr);
maxCPUnbrUser=max(DataInput(Node).CPUnbr)+1;
- disp(['Hardware has ', num2str(RealCPUnbr),' Cpu/Cores!']);
- disp(['User requires ',num2str(CPUnbrUser),' Cpu/Cores!']);
+ disp(['Hardware has ', num2str(RealCPUnbr),' Cpu/Cores!'])
+ disp(['User requires ',num2str(CPUnbrUser),' Cpu/Cores!'])
if CPUnbrUser==RealCPUnbr,
% It is Ok!
- disp('Check on CPUnbr Variable ..... Ok!');
- disp(' ');
- disp(' ');
- disp(' ');
-
+ disp('Check on CPUnbr Variable ..... Ok!')
+ skipline(3)
end
if CPUnbrUser > RealCPUnbr
- disp('Warning! The user asks to use more CPU''s than those available.');
- disp(' ');
- disp(' ');
+ disp('Warning! The user asks to use more CPU''s than those available.')
+ skipline(2)
ErrorCode=2.1;
- % return
-
end
if CPUnbrUser < RealCPUnbr
- disp('Warning! There are unused CPU''s!');
- disp(' ');
- disp(' ');
+ disp('Warning! There are unused CPU''s!')
+ skipline(2)
ErrorCode=2.2;
- % return
end
- disp(['Test for Cluster computation, computer ',DataInput(Node).ComputerName, ' ..... Passed!']);
- disp(' ');
- disp(' ');
-
-
-end
-
-return
\ No newline at end of file
+ disp(['Test for Cluster computation, computer ',DataInput(Node).ComputerName, ' ..... Passed!'])
+ skipline(2)
+end
\ No newline at end of file
diff --git a/matlab/plot_identification.m b/matlab/plot_identification.m
index b371295101f959a3533dfc3ff74eaf0bbe1ab826..278133ce76c5988cab30976164c65e3f0cf27ec3 100644
--- a/matlab/plot_identification.m
+++ b/matlab/plot_identification.m
@@ -88,7 +88,7 @@ if SampleSize == 1,
if advanced,
if ~options_.nodisplay,
- disp(' ')
+ skipline()
disp('Press ENTER to plot advanced diagnostics'), pause(5),
end
hh = dyn_figure(options_,'Name',[tittxt, ' - Sensitivity plot']);
@@ -152,7 +152,7 @@ if SampleSize == 1,
xlabel([tittxt,' - Collinearity patterns with ', int2str(j) ,' parameter(s)'],'interpreter','none')
dyn_saveas(hh,[ IdentifDirectoryName '/' M_.fname '_ident_collinearity_' tittxt1 '_' int2str(j) ],options_);
end
- disp('')
+ skipline()
if idehess.flag_score,
[U,S,V]=svd(idehess.AHess,0);
S=diag(S);
@@ -232,7 +232,7 @@ else
dyn_saveas(hh,[ IdentifDirectoryName '/' M_.fname '_MC_sensitivity' ],options_);
if advanced,
if ~options_.nodisplay,
- disp(' ')
+ skipline()
disp('Press ENTER to display advanced diagnostics'), pause(5),
end
% options_.nograph=1;
diff --git a/matlab/random_walk_metropolis_hastings.m b/matlab/random_walk_metropolis_hastings.m
index f64603f69e7fa491f42b772822a97f6231606cc7..91cd6953479ed0a0218144d1eade0217d701791b 100644
--- a/matlab/random_walk_metropolis_hastings.m
+++ b/matlab/random_walk_metropolis_hastings.m
@@ -168,4 +168,4 @@ disp(['MH: Total number of generated files : ' int2str(NewFile(1)*nblck) '.
disp(['MH: Total number of iterations : ' int2str((NewFile(1)-1)*MAX_nruns+irun-1) '.'])
disp('MH: average acceptation rate per chain : ')
disp(record.AcceptationRates);
-disp(' ')
+skipline()
diff --git a/matlab/resid.m b/matlab/resid.m
index 807bb435f4407b9bb8cdea34a8d7c49704b4d23f..a69ba8fe3cfc71932689b46236df3802456e697c 100644
--- a/matlab/resid.m
+++ b/matlab/resid.m
@@ -83,12 +83,10 @@ M_.Sigma_e = Sigma_e;
% Display the non-zero residuals if no return value
if nargout == 0
- for i = 1:4
- disp(' ')
- end
+ skipline(4)
ind = [];
disp('Residuals of the static equations:')
- disp(' ')
+ skipline()
for i=1:M_.orig_endo_nbr
if abs(z(i)) < options_.dynatol.f/100
tmp = 0;
@@ -107,9 +105,7 @@ if nargout == 0
disp( ['Equation number ', int2str(i) ,' : ', num2str(tmp) ,' : ' s])
end
end
- for i = 1:2
- disp(' ')
- end
+ skipline(2)
end
if info(1)
diff --git a/matlab/set_dynare_seed.m b/matlab/set_dynare_seed.m
index c9eb42a9af6fec48bbab52ddd95a51501a7dccbd..991b8ed57bb19408b0684108d3bc9940e972bae6 100644
--- a/matlab/set_dynare_seed.m
+++ b/matlab/set_dynare_seed.m
@@ -73,9 +73,9 @@ if matlab_random_streams% Use new matlab interface.
strcmpi(a,'swb2712') )
disp('set_dynare_seed:: First argument must be string designing the uniform random number algorithm!')
RandStream.list
- disp(' ')
+ skipline()
disp('set_dynare_seed:: Change the first input accordingly...')
- disp(' ')
+ skipline()
error(' ')
end
if ~isint(b)
diff --git a/matlab/simplex_optimization_routine.m b/matlab/simplex_optimization_routine.m
index 5c19b270d7845f4a7ad496d8778a33ccd8141cd3..b06135c62ec9ab9fdbd10d5784c8d2a6a97c5994 100644
--- a/matlab/simplex_optimization_routine.m
+++ b/matlab/simplex_optimization_routine.m
@@ -167,11 +167,11 @@ trend_vector_2 = 2:(number_of_variables+1);
% Set initial simplex around the initial guess (x).
if verbose
- for i=1:3, disp(' '), end
+ skipline(3)
disp('+----------------------+')
disp(' SIMPLEX INITIALIZATION ')
disp('+----------------------+')
- disp(' ')
+ skipline()
end
initial_point = x;
[initial_score,junk1,junk2,nopenalty] = feval(objective_function,x,varargin{:});
@@ -188,7 +188,7 @@ else
for i=1:number_of_variables
fprintf(1,'%s: \t\t\t %+8.6f \t\t\t %+8.6f \t\t\t %+8.6f \t\t\t %+8.6f \t\t\t %+8.6f \n',bayestopt_.name{i},v(i,1), v(i,end), mean(v(i,:),2), min(v(i,:),[],2), max(v(i,:),[],2));
end
- disp(' ')
+ skipline()
end
end
@@ -247,8 +247,7 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
if fxe < fxr% xe is even better than xr.
if optimize_expansion_parameter
if verbose>1
- disp('')
- disp('')
+ skipline(2)
disp('Compute optimal expansion...')
end
xee = xbar + rho*chi*1.01*(xbar-v(:,end));
@@ -316,8 +315,7 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
end
if verbose>1
disp('Done!')
- disp(' ')
- disp(' ')
+ skipline(2)
end
end
v(:,end) = xe;
@@ -384,7 +382,7 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
disp(['Norm of dSimplex: ' num2str(norm(v-vold,'fro'))])
disp(['Crit. f: ' num2str(critF)])
disp(['Crit. x: ' num2str(critX)])
- disp(' ')
+ skipline()
end
if verbose && max(abs(best_point-v(:,1)))>x_tolerance;
if verbose<2
@@ -395,14 +393,14 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
disp(['Norm of dSimplex: ' num2str(norm(v-vold,'fro'))])
disp(['Crit. f: ' num2str(critF)])
disp(['Crit. x: ' num2str(critX)])
- disp(' ')
+ skipline()
end
disp(['Current parameter values: '])
fprintf(1,'%s: \t\t\t %s \t\t\t %s \t\t\t %s \t\t\t %s \t\t\t %s \n','Names','Best point', 'Worst point', 'Mean values', 'Min values', 'Max values');
for i=1:number_of_variables
fprintf(1,'%s: \t\t\t %+8.6f \t\t\t %+8.6f \t\t\t %+8.6f \t\t\t %+8.6f \t\t\t %+8.6f \n',bayestopt_.name{i}, v(i,1), v(i,end), mean(v(i,:),2), min(v(i,:),[],2), max(v(i,:),[],2));
end
- disp(' ')
+ skipline()
end
if abs(best_point_score-fv(1))<f_tolerance
no_improvements = no_improvements+1;
@@ -436,8 +434,7 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
iter_no_improvement_break = iter_no_improvement_break + 1;
simplex_init = simplex_init+1;
simplex_iterations = simplex_iterations+1;
- disp(' ')
- disp(' ')
+ skipline(2)
end
end
if ((func_count==max_func_calls) || (iter_count==max_iterations) || (iter_no_improvement_break==max_no_improvement_break) || convergence || tooslow)
@@ -486,8 +483,7 @@ while (func_count < max_func_calls) && (iter_count < max_iterations) && (simplex
iter_count = iter_count+1;
simplex_iterations = simplex_iterations+1;
simplex_algo_iterations = simplex_algo_iterations+1;
- disp(' ')
- disp(' ')
+ skipline(2)
else
break
end
diff --git a/matlab/simulated_moments_estimation.m b/matlab/simulated_moments_estimation.m
index 74b30f78aa583c088786e278fe21accd99f52a76..314122d835c145c75adb8d236dbf6469c130c40e 100644
--- a/matlab/simulated_moments_estimation.m
+++ b/matlab/simulated_moments_estimation.m
@@ -113,13 +113,13 @@ if nargin>2
estimated_parameters_optimization_path = [NaN;xparam];
save('optimization_path.mat','estimated_parameters_optimization_path');
end
- disp(' ')
+ skipline()
disp('Master talks to its slaves...')
- disp(' ')
+ skipline()
% Save the workspace.
save('master_variables.mat','options_','M_','oo_');
% Send the workspace to each remote computer.
- disp('')
+ skipline()
for i = 1:length(parallel)
if ~strcmpi(hostname,parallel(i).machine)
unix(['scp master_variables.mat ' , parallel(i).login , '@' , parallel(i).machine , ':' parallel(i).folder]);
@@ -191,9 +191,9 @@ if nargin>2
end
end
end
- disp(' ')
+ skipline()
disp('... And slaves do as ordered.')
- disp(' ')
+ skipline()
if exist('intermediary_results_from_master_and_slaves','dir')
unix('rm -rf intermediary_results_from_master_and_slaves');
end
@@ -201,7 +201,7 @@ if nargin>2
unix('chmod -R u+x intermediary_results_from_master_and_slaves');
end
-disp('');
+skipline()
if options.optimization_routine==1
% Set options for csminwel.
diff --git a/matlab/utilities/general/skipline.m b/matlab/skipline.m
similarity index 100%
rename from matlab/utilities/general/skipline.m
rename to matlab/skipline.m
diff --git a/matlab/solve1.m b/matlab/solve1.m
index 52eb8460e6193b1b84179b54b875290216068113..0cacf6e3adab630d50b17ecb5807b453ef0ba589 100644
--- a/matlab/solve1.m
+++ b/matlab/solve1.m
@@ -136,7 +136,7 @@ for its = 1:maxit
end
check = 1;
-disp(' ')
+skipline()
disp('SOLVE: maxit has been reached')
% 01/14/01 MJ lnsearch is now a separate function
diff --git a/matlab/steady.m b/matlab/steady.m
index 510d1f89f9fa597055fafb9952e108846937c4a1..5ae9a0ac9f501e3219eb6b95e2983d9468502bad 100644
--- a/matlab/steady.m
+++ b/matlab/steady.m
@@ -55,7 +55,7 @@ end
if info(1)
hv = options_.homotopy_values;
- disp(' ')
+ skipline()
disp('WARNING: homotopy step was not completed')
disp('The last values for which a solution was found are:')
for i=1:length(ip)
diff --git a/matlab/stoch_simul.m b/matlab/stoch_simul.m
index bf22883d9f5b15f0618805d6ea314f910983a085..8de0e4bfe9bff619d637ccbe885e08afe02e6fdd 100644
--- a/matlab/stoch_simul.m
+++ b/matlab/stoch_simul.m
@@ -83,9 +83,9 @@ if info(1)
end
if ~options_.noprint
- disp(' ')
+ skipline()
disp('MODEL SUMMARY')
- disp(' ')
+ skipline()
disp([' Number of variables: ' int2str(M_.endo_nbr)])
disp([' Number of stochastic shocks: ' int2str(M_.exo_nbr)])
disp([' Number of state variables: ' int2str(M_.nspred)])
@@ -97,9 +97,9 @@ if ~options_.noprint
lh = size(labels,2)+2;
dyntable(my_title,headers,labels,M_.Sigma_e,lh,10,6);
if options_.partial_information
- disp(' ')
+ skipline()
disp('SOLUTION UNDER PARTIAL INFORMATION')
- disp(' ')
+ skipline()
if isfield(options_,'varobs')&& ~isempty(options_.varobs)
PCL_varobs=options_.varobs;
@@ -113,7 +113,7 @@ if ~options_.noprint
disp([' ' PCL_varobs(i,:)])
end
end
- disp(' ')
+ skipline()
if options_.order <= 2 && ~PI_PCL_solver
disp_dr(oo_.dr,options_.order,var_list);
end
diff --git a/matlab/utilities/dataset/initialize_dataset.m b/matlab/utilities/dataset/initialize_dataset.m
index f43bee9bea5e2f81fe9d9b9eeb6d1b6b02f4222d..c890e83fde9b47a713c3fa4dde55f5327a766a04 100644
--- a/matlab/utilities/dataset/initialize_dataset.m
+++ b/matlab/utilities/dataset/initialize_dataset.m
@@ -48,10 +48,10 @@ dataset_.info.varobs = varobs;
% Test the number of variables in the database.
if dataset_.info.nvobs-size(rawdata,2)
- disp(' ')
+ skipline()
disp(['Declared number of observed variables = ' int2str(dataset.info.nvobs)])
disp(['Number of variables in the database = ' int2str(size(rawdata,2))])
- disp(' ')
+ skipline()
error(['Estimation can''t take place because the declared number of observed' ...
'variables doesn''t match the number of variables in the database.'])
end
diff --git a/matlab/utilities/doc/dynInfo.m b/matlab/utilities/doc/dynInfo.m
index 3c20d0e77065cbdd449bcece891cc31eae14f1e2..952c5bbe16d515c8a24ef32411386babba337e40 100644
--- a/matlab/utilities/doc/dynInfo.m
+++ b/matlab/utilities/doc/dynInfo.m
@@ -68,8 +68,7 @@ if strcmp(ext(2:end),'m')
fprintf(fid,'%s\n',deblank(block(i,:)));
end
fclose(fid);
- disp(' ')
- disp(' ')
+ skipline(2)
system(['makeinfo --plaintext --no-split --no-validate ' fun '.texi']);
delete([fun '.texi']);
else