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Encoding fixes.

time-shift
Stéphane Adjemian (Charybdis) 2019-11-25 11:48:09 +01:00
parent 75a929051f
commit 7e7f57d7d1
5 changed files with 892 additions and 892 deletions
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4
matlab/surgibbs.m
View File

@ -132,7 +132,7 @@ oo_.surgibbs.(model_name).posterior.mean.beta = (sum(oo_.surgibbs.(model_name).b
oo_.surgibbs.(model_name).posterior.variance.beta = cov(oo_.surgibbs.(model_name).betadraws); oo_.surgibbs.(model_name).posterior.variance.beta = cov(oo_.surgibbs.(model_name).betadraws);
% Yhat % Yhat
oo_.surgibbs.(model_name).Yhat = X*oo_.surgibbs.(model_name).posterior.mean.beta; oo_.surgibbs.(model_name).Yhat = X*oo_.surgibbs.(model_name).posterior.mean.beta;
% Residuals % Residuals
oo_.surgibbs.(model_name).resid = Y - oo_.surgibbs.(model_name).Yhat; oo_.surgibbs.(model_name).resid = Y - oo_.surgibbs.(model_name).Yhat;
@ -181,7 +181,7 @@ if ~options_.noprint
sprintf('No. Equations: %d', oo_.surgibbs.(model_name).neqs), ... sprintf('No. Equations: %d', oo_.surgibbs.(model_name).neqs), ...
sprintf('No. Independent Variables: %d', size(X, 2)), ... sprintf('No. Independent Variables: %d', size(X, 2)), ...
sprintf('Observations: %d', oo_.surgibbs.(model_name).dof)}; sprintf('Observations: %d', oo_.surgibbs.(model_name).dof)};
afterward = {sprintf('s^2: %f', oo_.surgibbs.(model_name).s2), sprintf('R^2: %f', oo_.surgibbs.(model_name).R2)}; afterward = {sprintf('s^2: %f', oo_.surgibbs.(model_name).s2), sprintf('R^2: %f', oo_.surgibbs.(model_name).R2)};
dyn_table(ttitle, preamble, afterward, param_names,... dyn_table(ttitle, preamble, afterward, param_names,...
{'Posterior mean', 'Posterior std.'}, 4,... {'Posterior mean', 'Posterior std.'}, 4,...

446
tests/ecb/SUR/panel_var_diff_NB_simulation_test.mod
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@ -1,223 +1,223 @@
// --+ options: json=compute +-- // --+ options: json=compute +--
/* REMARK /* REMARK
** ------ ** ------
** **
** You need to have the first line on top of the mod file. The options defined on this line are passed ** You need to have the first line on top of the mod file. The options defined on this line are passed
** to the dynare command (you can add other options, separated by spaces or commas). The option defined ** to the dynare command (you can add other options, separated by spaces or commas). The option defined
** here is mandatory for the decomposition. It forces Dynare to output another representation of the ** here is mandatory for the decomposition. It forces Dynare to output another representation of the
** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations. ** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations.
*/ */
var var
U2_Q_YED U2_Q_YED
U2_G_YER U2_G_YER
U2_STN U2_STN
U2_ESTN U2_ESTN
U2_EHIC U2_EHIC
DE_Q_YED DE_Q_YED
DE_G_YER DE_G_YER
DE_EHIC DE_EHIC
; ;
varexo varexo
res_U2_Q_YED res_U2_Q_YED
res_U2_G_YER res_U2_G_YER
res_U2_STN res_U2_STN
res_U2_ESTN res_U2_ESTN
res_U2_EHIC res_U2_EHIC
res_DE_Q_YED res_DE_Q_YED
res_DE_G_YER res_DE_G_YER
res_DE_EHIC res_DE_EHIC
; ;
parameters parameters
u2_q_yed_ecm_u2_q_yed_L1 u2_q_yed_ecm_u2_q_yed_L1
u2_q_yed_ecm_u2_stn_L1 u2_q_yed_ecm_u2_stn_L1
u2_q_yed_u2_g_yer_L1 u2_q_yed_u2_g_yer_L1
u2_q_yed_u2_stn_L1 u2_q_yed_u2_stn_L1
u2_g_yer_ecm_u2_q_yed_L1 u2_g_yer_ecm_u2_q_yed_L1
u2_g_yer_ecm_u2_stn_L1 u2_g_yer_ecm_u2_stn_L1
u2_g_yer_u2_q_yed_L1 u2_g_yer_u2_q_yed_L1
u2_g_yer_u2_g_yer_L1 u2_g_yer_u2_g_yer_L1
u2_g_yer_u2_stn_L1 u2_g_yer_u2_stn_L1
u2_stn_ecm_u2_q_yed_L1 u2_stn_ecm_u2_q_yed_L1
u2_stn_ecm_u2_stn_L1 u2_stn_ecm_u2_stn_L1
u2_stn_u2_q_yed_L1 u2_stn_u2_q_yed_L1
u2_stn_u2_g_yer_L1 u2_stn_u2_g_yer_L1
u2_estn_u2_estn_L1 u2_estn_u2_estn_L1
u2_ehic_u2_ehic_L1 u2_ehic_u2_ehic_L1
de_q_yed_ecm_de_q_yed_L1 de_q_yed_ecm_de_q_yed_L1
de_q_yed_ecm_u2_stn_L1 de_q_yed_ecm_u2_stn_L1
de_q_yed_de_g_yer_L1 de_q_yed_de_g_yer_L1
de_q_yed_u2_stn_L1 de_q_yed_u2_stn_L1
de_g_yer_ecm_de_q_yed_L1 de_g_yer_ecm_de_q_yed_L1
de_g_yer_ecm_u2_stn_L1 de_g_yer_ecm_u2_stn_L1
de_g_yer_de_q_yed_L1 de_g_yer_de_q_yed_L1
de_g_yer_de_g_yer_L1 de_g_yer_de_g_yer_L1
de_g_yer_u2_stn_L1 de_g_yer_u2_stn_L1
de_ehic_de_ehic_L1 de_ehic_de_ehic_L1
; ;
u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ; u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ;
u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ; u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ;
u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ; u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ;
u2_q_yed_u2_stn_L1 = 0.058397703958446 ; u2_q_yed_u2_stn_L1 = 0.058397703958446 ;
u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ; u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ;
u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ; u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ;
u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ; u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ;
u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ; u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ;
u2_g_yer_u2_stn_L1 = -0.0722359286123494 ; u2_g_yer_u2_stn_L1 = -0.0722359286123494 ;
u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ; u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ;
u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ; u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ;
u2_stn_u2_q_yed_L1 = 0.0328744983772825 ; u2_stn_u2_q_yed_L1 = 0.0328744983772825 ;
u2_stn_u2_g_yer_L1 = 0.292121949736756 ; u2_stn_u2_g_yer_L1 = 0.292121949736756 ;
u2_estn_u2_estn_L1 = 1 ; u2_estn_u2_estn_L1 = 1 ;
u2_ehic_u2_ehic_L1 = 1 ; u2_ehic_u2_ehic_L1 = 1 ;
de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ; de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ;
de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ; de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ;
de_q_yed_de_g_yer_L1 = 0.0401361895021082 ; de_q_yed_de_g_yer_L1 = 0.0401361895021082 ;
de_q_yed_u2_stn_L1 = 0.0583977039584461 ; de_q_yed_u2_stn_L1 = 0.0583977039584461 ;
de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ; de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ;
de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ; de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ;
de_g_yer_de_q_yed_L1 = 0.00376679676320256; de_g_yer_de_q_yed_L1 = 0.00376679676320256;
de_g_yer_de_g_yer_L1 = 0.480506381923643 ; de_g_yer_de_g_yer_L1 = 0.480506381923643 ;
de_g_yer_u2_stn_L1 = -0.0722359286123494 ; de_g_yer_u2_stn_L1 = -0.0722359286123494 ;
de_ehic_de_ehic_L1 = 1 ; de_ehic_de_ehic_L1 = 1 ;
model(linear); model(linear);
[name = 'eq1'] [name = 'eq1']
diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + u2_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_Q_YED ; + res_U2_Q_YED ;
[name = 'eq2'] [name = 'eq2']
diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + u2_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_G_YER ; + res_U2_G_YER ;
[name = 'eq3'] [name = 'eq3']
diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ res_U2_STN ; + res_U2_STN ;
[name = 'eq4'] [name = 'eq4']
U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1) U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1)
+ res_U2_ESTN ; + res_U2_ESTN ;
[name = 'eq5'] [name = 'eq5']
U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1) U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1)
+ res_U2_EHIC ; + res_U2_EHIC ;
[name = 'eq6'] [name = 'eq6']
diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + de_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_Q_YED ; + res_DE_Q_YED ;
[name = 'eq7'] [name = 'eq7']
diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1)) + de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1))
+ de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + de_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_G_YER ; + res_DE_G_YER ;
[name = 'eq8'] [name = 'eq8']
DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ; DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ;
end; end;
shocks; shocks;
var res_U2_Q_YED = 0.005; var res_U2_Q_YED = 0.005;
var res_U2_G_YER = 0.005; var res_U2_G_YER = 0.005;
var res_U2_STN = 0.005; var res_U2_STN = 0.005;
var res_U2_ESTN = 0.005; var res_U2_ESTN = 0.005;
var res_U2_EHIC = 0.005; var res_U2_EHIC = 0.005;
var res_DE_Q_YED = 0.005; var res_DE_Q_YED = 0.005;
var res_DE_G_YER = 0.005; var res_DE_G_YER = 0.005;
var res_DE_EHIC = 0.005; var res_DE_EHIC = 0.005;
end; end;
NSIMS = 1; NSIMS = 1;
options_.noprint = 1; options_.noprint = 1;
calibrated_values = M_.params; calibrated_values = M_.params;
verbatim; verbatim;
Sigma_e = M_.Sigma_e; Sigma_e = M_.Sigma_e;
end; end;
options_.bnlms.set_dynare_seed_to_default = false; options_.bnlms.set_dynare_seed_to_default = false;
nparampool = length(M_.params); nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool); BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS for i=1:NSIMS
firstobs = rand(3, length(M_.endo_names)); firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values; M_.params = calibrated_values;
M_.Sigma_e = Sigma_e; M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000); simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000)); simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*'); names=regexp(simdata.name, 'res\w*');
idxs = []; idxs = [];
for j=1:length(names) for j=1:length(names)
if isempty(names{j}) if isempty(names{j})
idxs = [idxs j]; idxs = [idxs j];
end end
end end
simdata = sur(simdata{idxs}); simdata = sur(simdata{idxs});
BETA(i, :) = M_.params'; BETA(i, :) = M_.params';
oo_ = rmfield(oo_, 'sur'); oo_ = rmfield(oo_, 'sur');
end end
if NSIMS > 1 if NSIMS > 1
if max(abs(mean(BETA)' - calibrated_values)) > 1e-2 if max(abs(mean(BETA)' - calibrated_values)) > 1e-2
error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]); error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]);
end end
else else
good = [-0.826686196809409 good = [-0.826686196809409
-0.346753563700393 -0.346753563700393
0.063013991583949 0.063013991583949
0.074802596658698 0.074802596658698
-0.017440119721953 -0.017440119721953
-0.127090614348862 -0.127090614348862
0.025293280404460 0.025293280404460
0.524290302468866 0.524290302468866
-0.117611206771440 -0.117611206771440
-0.027776224547132 -0.027776224547132
-0.156590828735908 -0.156590828735908
0.054039707976331 0.054039707976331
0.276257666502046 0.276257666502046
1.000417289621684 1.000417289621684
0.999336865129450 0.999336865129450
-0.803258152338916 -0.803258152338916
-0.309594948488168 -0.309594948488168
0.051602756230521 0.051602756230521
0.039275481081030 0.039275481081030
0.024897596371662 0.024897596371662
-0.096310133845385 -0.096310133845385
-0.022630284059365 -0.022630284059365
0.461683465196454 0.461683465196454
-0.110278113383114 -0.110278113383114
1.000000000000000]; 1.000000000000000];
if max(abs(BETA' - good)) > 1e-14 if max(abs(BETA' - good)) > 1e-14
error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]); error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]);
end end
return return
end end
for i=1:nparampool for i=1:nparampool
figure figure
hold on hold on
title(strrep(M_.param_names(i,:), '_', '\_')); title(strrep(M_.param_names(i,:), '_', '\_'));
histogram(BETA(:,i),50); histogram(BETA(:,i),50);
line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r'); line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r');
hold off hold off
end end

444
tests/ecb/SUR/panel_var_diff_NB_simulation_zero_eq.mod
View File

@ -1,222 +1,222 @@
// --+ options: json=compute +-- // --+ options: json=compute +--
/* REMARK /* REMARK
** ------ ** ------
** **
** You need to have the first line on top of the mod file. The options defined on this line are passed ** You need to have the first line on top of the mod file. The options defined on this line are passed
** to the dynare command (you can add other options, separated by spaces or commas). The option defined ** to the dynare command (you can add other options, separated by spaces or commas). The option defined
** here is mandatory for the decomposition. It forces Dynare to output another representation of the ** here is mandatory for the decomposition. It forces Dynare to output another representation of the
** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations. ** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations.
*/ */
var var
U2_Q_YED U2_Q_YED
U2_G_YER U2_G_YER
U2_STN U2_STN
U2_ESTN U2_ESTN
U2_EHIC U2_EHIC
DE_Q_YED DE_Q_YED
DE_G_YER DE_G_YER
DE_EHIC DE_EHIC
; ;
varexo varexo
res_U2_Q_YED res_U2_Q_YED
res_U2_G_YER res_U2_G_YER
res_U2_STN res_U2_STN
res_DE_Q_YED res_DE_Q_YED
res_DE_G_YER res_DE_G_YER
res_DE_EHIC res_DE_EHIC
; ;
parameters parameters
u2_q_yed_ecm_u2_q_yed_L1 u2_q_yed_ecm_u2_q_yed_L1
u2_q_yed_ecm_u2_stn_L1 u2_q_yed_ecm_u2_stn_L1
u2_q_yed_u2_g_yer_L1 u2_q_yed_u2_g_yer_L1
u2_q_yed_u2_stn_L1 u2_q_yed_u2_stn_L1
u2_g_yer_ecm_u2_q_yed_L1 u2_g_yer_ecm_u2_q_yed_L1
u2_g_yer_ecm_u2_stn_L1 u2_g_yer_ecm_u2_stn_L1
u2_g_yer_u2_q_yed_L1 u2_g_yer_u2_q_yed_L1
u2_g_yer_u2_g_yer_L1 u2_g_yer_u2_g_yer_L1
u2_g_yer_u2_stn_L1 u2_g_yer_u2_stn_L1
u2_stn_ecm_u2_q_yed_L1 u2_stn_ecm_u2_q_yed_L1
u2_stn_ecm_u2_stn_L1 u2_stn_ecm_u2_stn_L1
u2_stn_u2_q_yed_L1 u2_stn_u2_q_yed_L1
u2_stn_u2_g_yer_L1 u2_stn_u2_g_yer_L1
u2_estn_u2_estn_L1 u2_estn_u2_estn_L1
u2_ehic_u2_ehic_L1 u2_ehic_u2_ehic_L1
de_q_yed_ecm_de_q_yed_L1 de_q_yed_ecm_de_q_yed_L1
de_q_yed_ecm_u2_stn_L1 de_q_yed_ecm_u2_stn_L1
de_q_yed_de_g_yer_L1 de_q_yed_de_g_yer_L1
de_q_yed_u2_stn_L1 de_q_yed_u2_stn_L1
de_g_yer_ecm_de_q_yed_L1 de_g_yer_ecm_de_q_yed_L1
de_g_yer_ecm_u2_stn_L1 de_g_yer_ecm_u2_stn_L1
de_g_yer_de_q_yed_L1 de_g_yer_de_q_yed_L1
de_g_yer_de_g_yer_L1 de_g_yer_de_g_yer_L1
de_g_yer_u2_stn_L1 de_g_yer_u2_stn_L1
de_ehic_de_ehic_L1 de_ehic_de_ehic_L1
; ;
u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ; u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ;
u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ; u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ;
u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ; u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ;
u2_q_yed_u2_stn_L1 = 0.058397703958446 ; u2_q_yed_u2_stn_L1 = 0.058397703958446 ;
u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ; u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ;
u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ; u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ;
u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ; u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ;
u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ; u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ;
u2_g_yer_u2_stn_L1 = -0.0722359286123494 ; u2_g_yer_u2_stn_L1 = -0.0722359286123494 ;
u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ; u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ;
u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ; u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ;
u2_stn_u2_q_yed_L1 = 0.0328744983772825 ; u2_stn_u2_q_yed_L1 = 0.0328744983772825 ;
u2_stn_u2_g_yer_L1 = 0.292121949736756 ; u2_stn_u2_g_yer_L1 = 0.292121949736756 ;
u2_estn_u2_estn_L1 = 1 ; u2_estn_u2_estn_L1 = 1 ;
u2_ehic_u2_ehic_L1 = 1 ; u2_ehic_u2_ehic_L1 = 1 ;
de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ; de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ;
de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ; de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ;
de_q_yed_de_g_yer_L1 = 0.0401361895021082 ; de_q_yed_de_g_yer_L1 = 0.0401361895021082 ;
de_q_yed_u2_stn_L1 = 0.0583977039584461 ; de_q_yed_u2_stn_L1 = 0.0583977039584461 ;
de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ; de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ;
de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ; de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ;
de_g_yer_de_q_yed_L1 = 0.00376679676320256; de_g_yer_de_q_yed_L1 = 0.00376679676320256;
de_g_yer_de_g_yer_L1 = 0.480506381923643 ; de_g_yer_de_g_yer_L1 = 0.480506381923643 ;
de_g_yer_u2_stn_L1 = -0.0722359286123494 ; de_g_yer_u2_stn_L1 = -0.0722359286123494 ;
de_ehic_de_ehic_L1 = 1 ; de_ehic_de_ehic_L1 = 1 ;
model(linear); model(linear);
[name = 'eq1'] [name = 'eq1']
diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + u2_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_Q_YED ; + res_U2_Q_YED ;
[name = 'eq2'] [name = 'eq2']
diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + u2_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_G_YER ; + res_U2_G_YER ;
[name = 'eq3'] [name = 'eq3']
diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ res_U2_STN ; + res_U2_STN ;
[name = 'eq4'] [name = 'eq4']
U2_ESTN = 0 ; U2_ESTN = 0 ;
[name = 'eq5'] [name = 'eq5']
U2_EHIC = 0 ; U2_EHIC = 0 ;
[name = 'eq6'] [name = 'eq6']
diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + de_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_Q_YED ; + res_DE_Q_YED ;
[name = 'eq7'] [name = 'eq7']
diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1)) + de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1))
+ de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + de_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_G_YER ; + res_DE_G_YER ;
[name = 'eq8'] [name = 'eq8']
DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ; DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ;
end; end;
shocks; shocks;
var res_U2_Q_YED = 0.005; var res_U2_Q_YED = 0.005;
var res_U2_G_YER = 0.005; var res_U2_G_YER = 0.005;
var res_U2_STN = 0.005; var res_U2_STN = 0.005;
var res_DE_Q_YED = 0.005; var res_DE_Q_YED = 0.005;
var res_DE_G_YER = 0.005; var res_DE_G_YER = 0.005;
var res_DE_EHIC = 0.005; var res_DE_EHIC = 0.005;
end; end;
NSIMS = 1; NSIMS = 1;
options_.noprint = 1; options_.noprint = 1;
calibrated_values = M_.params; calibrated_values = M_.params;
verbatim; verbatim;
Sigma_e = M_.Sigma_e; Sigma_e = M_.Sigma_e;
end; end;
options_.bnlms.set_dynare_seed_to_default = false; options_.bnlms.set_dynare_seed_to_default = false;
nparampool = length(M_.params); nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool); BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS for i=1:NSIMS
firstobs = rand(3, length(M_.endo_names)); firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values; M_.params = calibrated_values;
M_.Sigma_e = Sigma_e; M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000); simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000)); simdata = simdata(simdata.dates(5001:6000));
% fill zeroed-out variables with random data to ensure they are not being referenced % fill zeroed-out variables with random data to ensure they are not being referenced
simdata.U2_EHIC = dseries(rand(1000, 1), simdata.firstdate, 'U2_EHIC'); simdata.U2_EHIC = dseries(rand(1000, 1), simdata.firstdate, 'U2_EHIC');
simdata.U2_ESTN = dseries(rand(1000, 1), simdata.firstdate, 'U2_ESTN'); simdata.U2_ESTN = dseries(rand(1000, 1), simdata.firstdate, 'U2_ESTN');
names = regexp(simdata.name, 'res\w*'); names = regexp(simdata.name, 'res\w*');
idxs = []; idxs = [];
for j=1:length(names) for j=1:length(names)
if isempty(names{j}) if isempty(names{j})
idxs = [idxs j]; idxs = [idxs j];
end end
end end
simdata = sur(simdata{idxs}); simdata = sur(simdata{idxs});
BETA(i, :) = M_.params'; BETA(i, :) = M_.params';
oo_ = rmfield(oo_, 'sur'); oo_ = rmfield(oo_, 'sur');
end end
if NSIMS > 1 if NSIMS > 1
if max(abs(mean(BETA)' - calibrated_values)) > 1e-2 if max(abs(mean(BETA)' - calibrated_values)) > 1e-2
error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]); error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]);
end end
else else
good = [-0.806260229719792 good = [-0.806260229719792
-0.354371215026078 -0.354371215026078
0.067618717060638 0.067618717060638
0.088053231576354 0.088053231576354
-0.057161898696690 -0.057161898696690
-0.136999143481575 -0.136999143481575
0.052047088887385 0.052047088887385
0.524022502978068 0.524022502978068
-0.110211572532150 -0.110211572532150
-0.041415758049800 -0.041415758049800
-0.162997606880957 -0.162997606880957
0.091000830792721 0.091000830792721
0.281196660545012 0.281196660545012
1.000000000000000 1.000000000000000
1.000000000000000 1.000000000000000
-0.823354793011220 -0.823354793011220
-0.337521089381118 -0.337521089381118
0.025493177305917 0.025493177305917
0.059513905441361 0.059513905441361
0.016845886773011 0.016845886773011
-0.151537340795868 -0.151537340795868
0.004832174649536 0.004832174649536
0.430883913061161 0.430883913061161
-0.071743697511067 -0.071743697511067
1.000000000000000]; 1.000000000000000];
if max(abs(BETA' - good)) > 1e-14 if max(abs(BETA' - good)) > 1e-14
error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]); error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]);
end end
return return
end end
for i=1:nparampool for i=1:nparampool
figure figure
hold on hold on
title(strrep(M_.param_names(i,:), '_', '\_')); title(strrep(M_.param_names(i,:), '_', '\_'));
histogram(BETA(:,i),50); histogram(BETA(:,i),50);
line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r'); line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r');
hold off hold off
end end

446
tests/ecb/SUR/sur_noniterative.mod
View File

@ -1,223 +1,223 @@
// --+ options: json=compute +-- // --+ options: json=compute +--
/* REMARK /* REMARK
** ------ ** ------
** **
** You need to have the first line on top of the mod file. The options defined on this line are passed ** You need to have the first line on top of the mod file. The options defined on this line are passed
** to the dynare command (you can add other options, separated by spaces or commas). The option defined ** to the dynare command (you can add other options, separated by spaces or commas). The option defined
** here is mandatory for the decomposition. It forces Dynare to output another representation of the ** here is mandatory for the decomposition. It forces Dynare to output another representation of the
** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations. ** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations.
*/ */
var var
U2_Q_YED U2_Q_YED
U2_G_YER U2_G_YER
U2_STN U2_STN
U2_ESTN U2_ESTN
U2_EHIC U2_EHIC
DE_Q_YED DE_Q_YED
DE_G_YER DE_G_YER
DE_EHIC DE_EHIC
; ;
varexo varexo
res_U2_Q_YED res_U2_Q_YED
res_U2_G_YER res_U2_G_YER
res_U2_STN res_U2_STN
res_U2_ESTN res_U2_ESTN
res_U2_EHIC res_U2_EHIC
res_DE_Q_YED res_DE_Q_YED
res_DE_G_YER res_DE_G_YER
res_DE_EHIC res_DE_EHIC
; ;
parameters parameters
u2_q_yed_ecm_u2_q_yed_L1 u2_q_yed_ecm_u2_q_yed_L1
u2_q_yed_ecm_u2_stn_L1 u2_q_yed_ecm_u2_stn_L1
u2_q_yed_u2_g_yer_L1 u2_q_yed_u2_g_yer_L1
u2_q_yed_u2_stn_L1 u2_q_yed_u2_stn_L1
u2_g_yer_ecm_u2_q_yed_L1 u2_g_yer_ecm_u2_q_yed_L1
u2_g_yer_ecm_u2_stn_L1 u2_g_yer_ecm_u2_stn_L1
u2_g_yer_u2_q_yed_L1 u2_g_yer_u2_q_yed_L1
u2_g_yer_u2_g_yer_L1 u2_g_yer_u2_g_yer_L1
u2_g_yer_u2_stn_L1 u2_g_yer_u2_stn_L1
u2_stn_ecm_u2_q_yed_L1 u2_stn_ecm_u2_q_yed_L1
u2_stn_ecm_u2_stn_L1 u2_stn_ecm_u2_stn_L1
u2_stn_u2_q_yed_L1 u2_stn_u2_q_yed_L1
u2_stn_u2_g_yer_L1 u2_stn_u2_g_yer_L1
u2_estn_u2_estn_L1 u2_estn_u2_estn_L1
u2_ehic_u2_ehic_L1 u2_ehic_u2_ehic_L1
de_q_yed_ecm_de_q_yed_L1 de_q_yed_ecm_de_q_yed_L1
de_q_yed_ecm_u2_stn_L1 de_q_yed_ecm_u2_stn_L1
de_q_yed_de_g_yer_L1 de_q_yed_de_g_yer_L1
de_q_yed_u2_stn_L1 de_q_yed_u2_stn_L1
de_g_yer_ecm_de_q_yed_L1 de_g_yer_ecm_de_q_yed_L1
de_g_yer_ecm_u2_stn_L1 de_g_yer_ecm_u2_stn_L1
de_g_yer_de_q_yed_L1 de_g_yer_de_q_yed_L1
de_g_yer_de_g_yer_L1 de_g_yer_de_g_yer_L1
de_g_yer_u2_stn_L1 de_g_yer_u2_stn_L1
de_ehic_de_ehic_L1 de_ehic_de_ehic_L1
; ;
u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ; u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ;
u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ; u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ;
u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ; u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ;
u2_q_yed_u2_stn_L1 = 0.058397703958446 ; u2_q_yed_u2_stn_L1 = 0.058397703958446 ;
u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ; u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ;
u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ; u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ;
u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ; u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ;
u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ; u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ;
u2_g_yer_u2_stn_L1 = -0.0722359286123494 ; u2_g_yer_u2_stn_L1 = -0.0722359286123494 ;
u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ; u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ;
u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ; u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ;
u2_stn_u2_q_yed_L1 = 0.0328744983772825 ; u2_stn_u2_q_yed_L1 = 0.0328744983772825 ;
u2_stn_u2_g_yer_L1 = 0.292121949736756 ; u2_stn_u2_g_yer_L1 = 0.292121949736756 ;
u2_estn_u2_estn_L1 = 1 ; u2_estn_u2_estn_L1 = 1 ;
u2_ehic_u2_ehic_L1 = 1 ; u2_ehic_u2_ehic_L1 = 1 ;
de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ; de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ;
de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ; de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ;
de_q_yed_de_g_yer_L1 = 0.0401361895021082 ; de_q_yed_de_g_yer_L1 = 0.0401361895021082 ;
de_q_yed_u2_stn_L1 = 0.0583977039584461 ; de_q_yed_u2_stn_L1 = 0.0583977039584461 ;
de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ; de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ;
de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ; de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ;
de_g_yer_de_q_yed_L1 = 0.00376679676320256; de_g_yer_de_q_yed_L1 = 0.00376679676320256;
de_g_yer_de_g_yer_L1 = 0.480506381923643 ; de_g_yer_de_g_yer_L1 = 0.480506381923643 ;
de_g_yer_u2_stn_L1 = -0.0722359286123494 ; de_g_yer_u2_stn_L1 = -0.0722359286123494 ;
de_ehic_de_ehic_L1 = 1 ; de_ehic_de_ehic_L1 = 1 ;
model(linear); model(linear);
[name = 'eq1'] [name = 'eq1']
diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + u2_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_Q_YED ; + res_U2_Q_YED ;
[name = 'eq2'] [name = 'eq2']
diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + u2_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_G_YER ; + res_U2_G_YER ;
[name = 'eq3'] [name = 'eq3']
diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ res_U2_STN ; + res_U2_STN ;
[name = 'eq4'] [name = 'eq4']
U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1) U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1)
+ res_U2_ESTN ; + res_U2_ESTN ;
[name = 'eq5'] [name = 'eq5']
U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1) U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1)
+ res_U2_EHIC ; + res_U2_EHIC ;
[name = 'eq6'] [name = 'eq6']
diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + de_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_Q_YED ; + res_DE_Q_YED ;
[name = 'eq7'] [name = 'eq7']
diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1)) + de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1))
+ de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + de_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_G_YER ; + res_DE_G_YER ;
[name = 'eq8'] [name = 'eq8']
DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ; DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ;
end; end;
shocks; shocks;
var res_U2_Q_YED = 0.005; var res_U2_Q_YED = 0.005;
var res_U2_G_YER = 0.005; var res_U2_G_YER = 0.005;
var res_U2_STN = 0.005; var res_U2_STN = 0.005;
var res_U2_ESTN = 0.005; var res_U2_ESTN = 0.005;
var res_U2_EHIC = 0.005; var res_U2_EHIC = 0.005;
var res_DE_Q_YED = 0.005; var res_DE_Q_YED = 0.005;
var res_DE_G_YER = 0.005; var res_DE_G_YER = 0.005;
var res_DE_EHIC = 0.005; var res_DE_EHIC = 0.005;
end; end;
NSIMS = 1; NSIMS = 1;
options_.noprint = 1; options_.noprint = 1;
calibrated_values = M_.params; calibrated_values = M_.params;
verbatim; verbatim;
Sigma_e = M_.Sigma_e; Sigma_e = M_.Sigma_e;
end; end;
options_.bnlms.set_dynare_seed_to_default = false; options_.bnlms.set_dynare_seed_to_default = false;
nparampool = length(M_.params); nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool); BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS for i=1:NSIMS
firstobs = rand(3, length(M_.endo_names)); firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values; M_.params = calibrated_values;
M_.Sigma_e = Sigma_e; M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000); simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000)); simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*'); names=regexp(simdata.name, 'res\w*');
idxs = []; idxs = [];
for j=1:length(names) for j=1:length(names)
if isempty(names{j}) if isempty(names{j})
idxs = [idxs j]; idxs = [idxs j];
end end
end end
simdata = sur(simdata{idxs}, {}, {}, 'mymodel', true); simdata = sur(simdata{idxs}, {}, {}, 'mymodel', true);
BETA(i, :) = M_.params'; BETA(i, :) = M_.params';
oo_ = rmfield(oo_, 'sur'); oo_ = rmfield(oo_, 'sur');
end end
if NSIMS > 1 if NSIMS > 1
if max(abs(mean(BETA)' - calibrated_values)) > 1e-2 if max(abs(mean(BETA)' - calibrated_values)) > 1e-2
error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]); error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]);
end end
else else
good = [-0.826686383251952 good = [-0.826686383251952
-0.346754226737713 -0.346754226737713
0.063012625739192 0.063012625739192
0.074803008678581 0.074803008678581
-0.017406695286611 -0.017406695286611
-0.127075466955954 -0.127075466955954
0.025273119798253 0.025273119798253
0.524311285013928 0.524311285013928
-0.117653504652072 -0.117653504652072
-0.027795769946178 -0.027795769946178
-0.156599054434094 -0.156599054434094
0.054048691636616 0.054048691636616
0.276250884768198 0.276250884768198
1.000417819589230 1.000417819589230
0.999336022919911 0.999336022919911
-0.803262845969268 -0.803262845969268
-0.309598590696623 -0.309598590696623
0.051598925732525 0.051598925732525
0.039275097813797 0.039275097813797
0.024902442384228 0.024902442384228
-0.096310332265968 -0.096310332265968
-0.022625946626029 -0.022625946626029
0.461672601960238 0.461672601960238
-0.110232456667380 -0.110232456667380
1.000000000000000]; 1.000000000000000];
if max(abs(BETA' - good)) > 1e-14 if max(abs(BETA' - good)) > 1e-14
error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]); error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]);
end end
return return
end end
for i=1:nparampool for i=1:nparampool
figure figure
hold on hold on
title(strrep(M_.param_names(i,:), '_', '\_')); title(strrep(M_.param_names(i,:), '_', '\_'));
histogram(BETA(:,i),50); histogram(BETA(:,i),50);
line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r'); line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r');
hold off hold off
end end

444
tests/ecb/SUR/sur_params_noniterative.mod
View File

@ -1,222 +1,222 @@
// --+ options: json=compute +-- // --+ options: json=compute +--
/* REMARK /* REMARK
** ------ ** ------
** **
** You need to have the first line on top of the mod file. The options defined on this line are passed ** You need to have the first line on top of the mod file. The options defined on this line are passed
** to the dynare command (you can add other options, separated by spaces or commas). The option defined ** to the dynare command (you can add other options, separated by spaces or commas). The option defined
** here is mandatory for the decomposition. It forces Dynare to output another representation of the ** here is mandatory for the decomposition. It forces Dynare to output another representation of the
** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations. ** model in JSON file (additionaly to the matlab files) which is used here to manipulate the equations.
*/ */
var var
U2_Q_YED U2_Q_YED
U2_G_YER U2_G_YER
U2_STN U2_STN
U2_ESTN U2_ESTN
U2_EHIC U2_EHIC
DE_Q_YED DE_Q_YED
DE_G_YER DE_G_YER
DE_EHIC DE_EHIC
; ;
varexo varexo
res_U2_Q_YED res_U2_Q_YED
res_U2_G_YER res_U2_G_YER
res_U2_STN res_U2_STN
res_U2_ESTN res_U2_ESTN
res_U2_EHIC res_U2_EHIC
res_DE_Q_YED res_DE_Q_YED
res_DE_G_YER res_DE_G_YER
res_DE_EHIC res_DE_EHIC
; ;
parameters parameters
u2_q_yed_ecm_u2_q_yed_L1 u2_q_yed_ecm_u2_q_yed_L1
u2_q_yed_ecm_u2_stn_L1 u2_q_yed_ecm_u2_stn_L1
u2_q_yed_u2_g_yer_L1 u2_q_yed_u2_g_yer_L1
u2_q_yed_u2_stn_L1 u2_q_yed_u2_stn_L1
u2_g_yer_ecm_u2_q_yed_L1 u2_g_yer_ecm_u2_q_yed_L1
u2_g_yer_ecm_u2_stn_L1 u2_g_yer_ecm_u2_stn_L1
u2_g_yer_u2_q_yed_L1 u2_g_yer_u2_q_yed_L1
u2_g_yer_u2_g_yer_L1 u2_g_yer_u2_g_yer_L1
u2_g_yer_u2_stn_L1 u2_g_yer_u2_stn_L1
u2_stn_ecm_u2_q_yed_L1 u2_stn_ecm_u2_q_yed_L1
u2_stn_ecm_u2_stn_L1 u2_stn_ecm_u2_stn_L1
u2_stn_u2_q_yed_L1 u2_stn_u2_q_yed_L1
u2_stn_u2_g_yer_L1 u2_stn_u2_g_yer_L1
u2_estn_u2_estn_L1 u2_estn_u2_estn_L1
u2_ehic_u2_ehic_L1 u2_ehic_u2_ehic_L1
de_q_yed_ecm_de_q_yed_L1 de_q_yed_ecm_de_q_yed_L1
de_q_yed_ecm_u2_stn_L1 de_q_yed_ecm_u2_stn_L1
de_q_yed_de_g_yer_L1 de_q_yed_de_g_yer_L1
de_q_yed_u2_stn_L1 de_q_yed_u2_stn_L1
de_g_yer_ecm_de_q_yed_L1 de_g_yer_ecm_de_q_yed_L1
de_g_yer_ecm_u2_stn_L1 de_g_yer_ecm_u2_stn_L1
de_g_yer_de_q_yed_L1 de_g_yer_de_q_yed_L1
de_g_yer_de_g_yer_L1 de_g_yer_de_g_yer_L1
de_g_yer_u2_stn_L1 de_g_yer_u2_stn_L1
de_ehic_de_ehic_L1 de_ehic_de_ehic_L1
; ;
u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ; u2_q_yed_ecm_u2_q_yed_L1 = -0.82237516589315 ;
u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ; u2_q_yed_ecm_u2_stn_L1 = -0.323715338568976 ;
u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ; u2_q_yed_u2_g_yer_L1 = 0.0401361895021084 ;
u2_q_yed_u2_stn_L1 = 0.058397703958446 ; u2_q_yed_u2_stn_L1 = 0.058397703958446 ;
u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ; u2_g_yer_ecm_u2_q_yed_L1 = 0.0189896046977421 ;
u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ; u2_g_yer_ecm_u2_stn_L1 = -0.109597659887432 ;
u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ; u2_g_yer_u2_q_yed_L1 = 0.0037667967632025 ;
u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ; u2_g_yer_u2_g_yer_L1 = 0.480506381923644 ;
u2_g_yer_u2_stn_L1 = -0.0722359286123494 ; u2_g_yer_u2_stn_L1 = -0.0722359286123494 ;
u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ; u2_stn_ecm_u2_q_yed_L1 = -0.0438500662608356 ;
u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ; u2_stn_ecm_u2_stn_L1 = -0.153283917138772 ;
u2_stn_u2_q_yed_L1 = 0.0328744983772825 ; u2_stn_u2_q_yed_L1 = 0.0328744983772825 ;
u2_stn_u2_g_yer_L1 = 0.292121949736756 ; u2_stn_u2_g_yer_L1 = 0.292121949736756 ;
u2_estn_u2_estn_L1 = 1 ; u2_estn_u2_estn_L1 = 1 ;
u2_ehic_u2_ehic_L1 = 1 ; u2_ehic_u2_ehic_L1 = 1 ;
de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ; de_q_yed_ecm_de_q_yed_L1 = -0.822375165893149 ;
de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ; de_q_yed_ecm_u2_stn_L1 = -0.323715338568977 ;
de_q_yed_de_g_yer_L1 = 0.0401361895021082 ; de_q_yed_de_g_yer_L1 = 0.0401361895021082 ;
de_q_yed_u2_stn_L1 = 0.0583977039584461 ; de_q_yed_u2_stn_L1 = 0.0583977039584461 ;
de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ; de_g_yer_ecm_de_q_yed_L1 = 0.0189896046977422 ;
de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ; de_g_yer_ecm_u2_stn_L1 = -0.109597659887433 ;
de_g_yer_de_q_yed_L1 = 0.00376679676320256; de_g_yer_de_q_yed_L1 = 0.00376679676320256;
de_g_yer_de_g_yer_L1 = 0.480506381923643 ; de_g_yer_de_g_yer_L1 = 0.480506381923643 ;
de_g_yer_u2_stn_L1 = -0.0722359286123494 ; de_g_yer_u2_stn_L1 = -0.0722359286123494 ;
de_ehic_de_ehic_L1 = 1 ; de_ehic_de_ehic_L1 = 1 ;
model(linear); model(linear);
[name = 'eq1'] [name = 'eq1']
diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_Q_YED) = u2_q_yed_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_q_yed_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + u2_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_Q_YED ; + res_U2_Q_YED ;
[name = 'eq2'] [name = 'eq2']
diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_G_YER) = u2_g_yer_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_g_yer_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_g_yer_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ u2_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + u2_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_U2_G_YER ; + res_U2_G_YER ;
[name = 'eq3'] [name = 'eq3']
diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1)) diff(U2_STN) = u2_stn_ecm_u2_q_yed_L1 * (U2_Q_YED(-1) - U2_EHIC(-1))
+ u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + u2_stn_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1)) + u2_stn_u2_q_yed_L1 * diff(U2_Q_YED(-1))
+ u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1)) + u2_stn_u2_g_yer_L1 * diff(U2_G_YER(-1))
+ res_U2_STN ; + res_U2_STN ;
[name = 'eq4'] [name = 'eq4']
U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1) U2_ESTN = u2_estn_u2_estn_L1 * U2_ESTN(-1)
+ res_U2_ESTN ; + res_U2_ESTN ;
[name = 'eq5'] [name = 'eq5']
U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1) U2_EHIC = u2_ehic_u2_ehic_L1 * U2_EHIC(-1)
+ res_U2_EHIC ; + res_U2_EHIC ;
[name = 'eq6'] [name = 'eq6']
diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_Q_YED) = de_q_yed_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_q_yed_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_q_yed_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_q_yed_u2_stn_L1 * diff(U2_STN(-1)) + de_q_yed_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_Q_YED ; + res_DE_Q_YED ;
[name = 'eq7'] [name = 'eq7']
diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1)) diff(DE_G_YER) = de_g_yer_ecm_de_q_yed_L1 * (DE_Q_YED(-1) - DE_EHIC(-1))
+ de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1)) + de_g_yer_ecm_u2_stn_L1 * (U2_STN(-1) - U2_ESTN(-1))
+ de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1)) + de_g_yer_de_q_yed_L1 * diff(DE_Q_YED(-1))
+ de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1)) + de_g_yer_de_g_yer_L1 * diff(DE_G_YER(-1))
+ de_g_yer_u2_stn_L1 * diff(U2_STN(-1)) + de_g_yer_u2_stn_L1 * diff(U2_STN(-1))
+ res_DE_G_YER ; + res_DE_G_YER ;
[name = 'eq8'] [name = 'eq8']
DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ; DE_EHIC = DE_EHIC(-1) + res_DE_EHIC ;
end; end;
shocks; shocks;
var res_U2_Q_YED = 0.005; var res_U2_Q_YED = 0.005;
var res_U2_G_YER = 0.005; var res_U2_G_YER = 0.005;
var res_U2_STN = 0.005; var res_U2_STN = 0.005;
var res_U2_ESTN = 0.005; var res_U2_ESTN = 0.005;
var res_U2_EHIC = 0.005; var res_U2_EHIC = 0.005;
var res_DE_Q_YED = 0.005; var res_DE_Q_YED = 0.005;
var res_DE_G_YER = 0.005; var res_DE_G_YER = 0.005;
var res_DE_EHIC = 0.005; var res_DE_EHIC = 0.005;
end; end;
NSIMS = 1; NSIMS = 1;
options_.noprint = 1; options_.noprint = 1;
calibrated_values = M_.params; calibrated_values = M_.params;
verbatim; verbatim;
Sigma_e = M_.Sigma_e; Sigma_e = M_.Sigma_e;
end; end;
options_.bnlms.set_dynare_seed_to_default = false; options_.bnlms.set_dynare_seed_to_default = false;
nparampool = length(M_.params); nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool); BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS for i=1:NSIMS
firstobs = rand(3, length(M_.endo_names)); firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values; M_.params = calibrated_values;
M_.Sigma_e = Sigma_e; M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000); simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000)); simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*'); names=regexp(simdata.name, 'res\w*');
idxs = []; idxs = [];
for j=1:length(names) for j=1:length(names)
if isempty(names{j}) if isempty(names{j})
idxs = [idxs j]; idxs = [idxs j];
end end
end end
simdata = sur(simdata{idxs}, {'u2_q_yed_u2_g_yer_L1', 'u2_estn_u2_estn_L1', 'u2_ehic_u2_ehic_L1', 'de_q_yed_de_g_yer_L1', 'u2_g_yer_u2_g_yer_L1', 'u2_stn_u2_q_yed_L1', 'u2_q_yed_ecm_u2_q_yed_L1', 'de_g_yer_u2_stn_L1'}, {}, 'mymodel', true); simdata = sur(simdata{idxs}, {'u2_q_yed_u2_g_yer_L1', 'u2_estn_u2_estn_L1', 'u2_ehic_u2_ehic_L1', 'de_q_yed_de_g_yer_L1', 'u2_g_yer_u2_g_yer_L1', 'u2_stn_u2_q_yed_L1', 'u2_q_yed_ecm_u2_q_yed_L1', 'de_g_yer_u2_stn_L1'}, {}, 'mymodel', true);
BETA(i, :) = M_.params'; BETA(i, :) = M_.params';
oo_ = rmfield(oo_, 'sur'); oo_ = rmfield(oo_, 'sur');
end end
if NSIMS > 1 if NSIMS > 1
if max(abs(mean(BETA)' - calibrated_values)) > 1e-2 if max(abs(mean(BETA)' - calibrated_values)) > 1e-2
error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]); error(['sum(abs(mean(BETA)'' - calibrated_values)) ' num2str(sum(abs(mean(BETA)' - calibrated_values)))]);
end end
else else
good = [-0.811559435201128 good = [-0.811559435201128
-0.323715338568976 -0.323715338568976
0.073666282610569 0.073666282610569
0.058397703958446 0.058397703958446
0.018989604697742 0.018989604697742
-0.109597659887432 -0.109597659887432
0.003766796763203 0.003766796763203
0.510389966839712 0.510389966839712
-0.072235928612349 -0.072235928612349
-0.043850066260836 -0.043850066260836
-0.153283917138772 -0.153283917138772
0.058739144948151 0.058739144948151
0.292121949736756 0.292121949736756
1.000413662363949 1.000413662363949
0.999337514406012 0.999337514406012
-0.822375165893149 -0.822375165893149
-0.323715338568977 -0.323715338568977
0.046096335070402 0.046096335070402
0.058397703958446 0.058397703958446
0.018989604697742 0.018989604697742
-0.109597659887433 -0.109597659887433
0.003766796763203 0.003766796763203
0.480506381923643 0.480506381923643
-0.111002148299648 -0.111002148299648
1.000000000000000]; 1.000000000000000];
if max(abs(BETA' - good)) > 1e-14 if max(abs(BETA' - good)) > 1e-14
error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]); error(['sum of BETA'' - good was: ' num2str(sum(abs(BETA - good)))]);
end end
return return
end end
for i=1:nparampool for i=1:nparampool
figure figure
hold on hold on
title(strrep(M_.param_names(i,:), '_', '\_')); title(strrep(M_.param_names(i,:), '_', '\_'));
histogram(BETA(:,i),50); histogram(BETA(:,i),50);
line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r'); line([calibrated_values(i) calibrated_values(i)], [0 NSIMS/10], 'LineWidth', 2, 'Color', 'r');
hold off hold off
end end