1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
|
function oo_=evaluate_smoother(parameters,var_list)
% Evaluate the smoother at parameters.
%
% INPUTS
% o parameters a string ('posterior mode','posterior mean','posterior median','prior mode','prior mean') or a vector of values for
% the (estimated) parameters of the model.
% o var_list subset of endogenous variables
%
%
% OUTPUTS
% o oo [structure] results:
% - SmoothedVariables
% - SmoothedShocks
% - SmoothedVariables
% - SmoothedVariables
% - SmoothedVariables
% - SmoothedVariables
% - SmoothedVariables
% - SmoothedVariables
%
% SPECIAL REQUIREMENTS
% None
%
% REMARKS
% [1] This function use persistent variables for the dataset and the description of the missing observations. Consequently, if this function
% is called more than once (by changing the value of parameters) the sample *must not* change.
% Copyright (C) 2010-2013 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
global options_ M_ bayestopt_ oo_ estim_params_ % estim_params_ may be emty
persistent dataset_
if ischar(parameters) && strcmp(parameters,'calibration')
options_.smoother=1;
end
if isempty(dataset_) || isempty(bayestopt_)
[dataset_,xparam1, hh, M_, options_, oo_, estim_params_,bayestopt_] = dynare_estimation_init(var_list, M_.fname, [], M_, options_, oo_, estim_params_, bayestopt_);
end
if nargin==0
parameters = 'posterior_mode';
end
if ischar(parameters)
switch parameters
case 'posterior_mode'
parameters = get_posterior_parameters('mode');
case 'posterior_mean'
parameters = get_posterior_parameters('mean');
case 'posterior_median'
parameters = get_posterior_parameters('median');
case 'prior_mode'
parameters = bayestopt_.p5(:);
case 'prior_mean'
parameters = bayestopt_.p1;
case 'calibration'
if isempty(oo_.dr)
error('You must run ''stoch_simul'' first.');
end
parameters = [];
otherwise
disp('evaluate_smoother:: If the input argument is a string, then it has to be equal to:')
disp(' ''posterior_mode'', ')
disp(' ''posterior_mean'', ')
disp(' ''posterior_median'', ')
disp(' ''prior_mode'' or')
disp(' ''prior_mean''.')
disp(' ''calibration''.')
error
end
end
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp] = ...
DsgeSmoother(parameters,dataset_.info.ntobs,dataset_.data,dataset_.missing.aindex,dataset_.missing.state);
oo_.Smoother.SteadyState = ys;
oo_.Smoother.TrendCoeffs = trend_coeff;
if options_.filter_covariance
oo_.Smoother.Variance = P;
end
i_endo = bayestopt_.smoother_saved_var_list;
if options_.nk ~= 0
oo_.FilteredVariablesKStepAhead = ...
aK(options_.filter_step_ahead,i_endo,:);
if ~isempty(PK)
oo_.FilteredVariablesKStepAheadVariances = ...
PK(options_.filter_step_ahead,i_endo,i_endo,:);
end
if ~isempty(decomp)
oo_.FilteredVariablesShockDecomposition = ...
decomp(options_.filter_step_ahead,i_endo,:,:);
end
end
for i=bayestopt_.smoother_saved_var_list'
i1 = oo_.dr.order_var(bayestopt_.smoother_var_list(i));
eval(['oo_.SmoothedVariables.' deblank(M_.endo_names(i1,:)) ' = atT(i,:)'';']);
if options_.nk>0
eval(['oo_.FilteredVariables.' deblank(M_.endo_names(i1,:)) ' = squeeze(aK(1,i,:));']);
end
eval(['oo_.UpdatedVariables.' deblank(M_.endo_names(i1,:)) ' = updated_variables(i,:)'';']);
end
for i=1:M_.exo_nbr
eval(['oo_.SmoothedShocks.' deblank(M_.exo_names(i,:)) ' = innov(i,:)'';']);
end
|
