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Display estimation results PAC/NLS.

nls-fixes
Stéphane Adjemian (Ryûk) 2021-12-17 20:05:19 +01:00
parent 24c817afa7
commit 4512000f0f
Signed by: stepan
GPG Key ID: 295C1FE89E17EB3C
9 changed files with 75 additions and 101 deletions
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44
matlab/+estimate/nls.m
View File

@ -355,49 +355,11 @@ end
% Set options if provided as input arguments to nls routine.
oldopt = options_.optim_opt;
if nargin>5
if mod(nargin-5, 2)
error('Options must come by key/value pairs.')
end
i = 1;
while i<nargin-5
if isequal(varargin{i}, 'noprint')
noprint = varargin{i+1};
i = i+2;
continue
else
if ~exist('opt', 'var')
opt = sprintf('''%s''', varargin{i});
else
opt = sprintf('%s,''%s''', opt, varargin{i});
end
if isnumeric(varargin{i+1})
opt = sprintf('%s,%s', opt, num2str(varargin{i+1}));
else
opt = sprintf('%s,''%s''', opt, varargin{i+1});
end
i = i+2;
end
options_.optim_opt = opt;
end
end
if ~exist('opt', 'var')
options_.optim_opt = [];
end
if ~exist('noprint', 'var')
noprint = false;
end
if nargin<5
% If default optimization algorithm is used (csminwel), do not print
% iterations.
options_.optim_opt = '''verbosity'',0';
end
[noprint, opt] = opt4nls(varargin);
options_.optim_opt = opt;
%
% Check that we are able to evaluate the Sum of Squared Residuals on the initial guess
% Check that we are able to evaluate the Sum of uared Residuals on the initial guess
%
ssr0 = ssrfun(params0);

46
matlab/+pac/+estimate/nls.m
View File

@ -75,6 +75,8 @@ end
[pacmodl, lhs, rhs, pnames, enames, xnames, ~, pid, eid, xid, ~, ipnames_, params, data, islaggedvariables] = ...
pac.estimate.init(M_, oo_, eqname, params, data, range);
dLHS = M_.aux_vars(strmatch(lhs,M_.endo_names, 'exact')==[M_.aux_vars(:).endo_index]).orig_expr;
% Check that the error correction term is correct.
if M_.pac.(pacmodl).ec.istarget(2)
error(['\nThe error correction term in PAC equation (%s) is not correct.\nThe ' ...
@ -261,34 +263,8 @@ end
% Set options if provided as input arguments to nls routine.
oldopt = options_.optim_opt;
if nargin>5
if mod(nargin-5, 2)
error('Options must come by key/value pairs.')
end
i = 1;
opt = '';
while i<nargin-5
if i==1
opt = sprintf('''%s''', varargin{i});
else
opt = sprintf('%s,''%s''', opt, varargin{i});
end
if isnumeric(varargin{i+1})
opt = sprintf('%s,%s', opt, num2str(varargin{i+1}));
else
opt = sprintf('%s,''%s''', opt, varargin{i+1});
end
i = i+2;
end
options_.optim_opt = opt;
else
options_.optim_opt = [];
end
if nargin<5
% If default optimization algorithm is used (csminwel), do not print
% iterations.
options_.optim_opt = '''verbosity'',0';
end
[noprint, opt] = opt4nls(varargin);
options_.optim_opt = opt;
%
% Check that we are able to evaluate the Sum of Squared Residuals on the initial guess
@ -344,6 +320,7 @@ oo_.pac.(pacmodl).lhs = dseries(lhs, range(1), 'lhs');
oo_.pac.(pacmodl).fit = dseries(lhs-r, range(1), 'fit');
oo_.pac.(pacmodl).residual = dseries(r, range(1), 'residual');
oo_.pac.(pacmodl).ssr = SSR;
oo_.pac.(pacmodl).s2 = SSR/T;
oo_.pac.(pacmodl).R2 = 1-var(r)/var(lhs);
oo_.pac.(pacmodl).parnames = fieldnames(params);
oo_.pac.(pacmodl).estimator = params1;
@ -353,3 +330,16 @@ oo_.pac.(pacmodl).student = params1./(sqrt(diag(C)));
% Also save estimated parameters in M_
M_.params(ipnames_) = params1;
M_ = pac.update.parameters(pacmodl, M_, oo_, false);
if ~noprint
title = ['NLS Estimation of equation ''' eqname ''''];
preamble = {['Dependent Variable: ' dLHS], ...
sprintf('Observations: %d from %s to %s\n', (range(end)-range(1))+1, range(1).char, range(end).char)};
afterward = {sprintf('R^2: %f', oo_.pac.(pacmodl).R2), ...
sprintf('s^2: %f', oo_.pac.(pacmodl).s2)}; ...
dyn_table(title, preamble, afterward, oo_.pac.(pacmodl).parnames, ...
{'Estimates','t-statistic','Std. Error'}, 4, ...
[oo_.pac.(pacmodl).estimator oo_.pac.(pacmodl).student sqrt(diag(C))]);
end

1
matlab/dynare_config.m
View File

@ -71,6 +71,7 @@ p = {'/distributions/' ; ...
'/utilities/dataset/' ; ...
'/utilities/general/' ; ...
'/utilities/graphics/' ; ...
'/utilities/estimation/' ; ...
'/modules/reporting/src/' ; ...
'/modules/reporting/macros/'};

53
matlab/utilities/estimation/opt4nls.m Normal file
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@ -0,0 +1,53 @@
function [noprint, opt] = opt4nls(varargin)
% Sets options for NLS routines.
% Copyright © 021 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 <https://www.gnu.org/licenses/>.
varargin = varargin{1};
nargin = length(varargin);
noprint = false;
if nargin
if mod(nargin, 2)
error('Options must come by key/value pairs.')
end
i = 1;
while i<nargin
if isequal(varargin{i}, 'noprint')
noprint = varargin{i+1};
i = i+2;
continue
else
if ~exist('opt', 'var')
opt = sprintf('''%s''', varargin{i});
else
opt = sprintf('%s,''%s''', opt, varargin{i});
end
if isnumeric(varargin{i+1})
opt = sprintf('%s,%s', opt, num2str(varargin{i+1}));
else
opt = sprintf('%s,''%s''', opt, varargin{i+1});
end
i = i+2;
end
end
else
opt = '';
end

4
tests/pac/var-10e/example1.mod
View File

@ -96,8 +96,4 @@ e_c_m_nls = M_.params(strmatch('e_c_m', M_.param_names, 'exact'));
c_z_1_nls = M_.params(strmatch('c_z_1', M_.param_names, 'exact'));
c_z_2_nls = M_.params(strmatch('c_z_2', M_.param_names, 'exact'));
disp(sprintf('Estimate of e_c_m: %f', e_c_m_nls))
disp(sprintf('Estimate of c_z_1: %f', c_z_1_nls))
disp(sprintf('Estimate of c_z_2: %f', c_z_2_nls))
save('example1.estimation.mat', 'e_c_m_nls', 'c_z_1_nls', 'c_z_2_nls')

4
tests/pac/var-10e/example2.mod
View File

@ -80,10 +80,6 @@ e_c_m_nls = M_.params(strmatch('e_c_m', M_.param_names, 'exact'));
c_z_1_nls = M_.params(strmatch('c_z_1', M_.param_names, 'exact'));
c_z_2_nls = M_.params(strmatch('c_z_2', M_.param_names, 'exact'));
disp(sprintf('Estimate of e_c_m: %f', e_c_m_nls))
disp(sprintf('Estimate of c_z_1: %f', c_z_1_nls))
disp(sprintf('Estimate of c_z_2: %f', c_z_2_nls))
% Check consistency with disaggregated target
ts1 = dseries('example1.data.mat');
ts2 = dseries('example2.data.mat');

8
tests/pac/var-11e/example1.mod
View File

@ -90,11 +90,3 @@ eparams.c_z_2 = .2;
edata = TrueData;
edata.ez = dseries(NaN(TrueData.nobs, 1), 2000Q1, 'ez');
pac.estimate.nls('zpac', eparams, edata, 2005Q1:2005Q1+4000, 'fmincon');
e_c_m_nls = M_.params(strmatch('e_c_m', M_.param_names, 'exact'));
c_z_1_nls = M_.params(strmatch('c_z_1', M_.param_names, 'exact'));
c_z_2_nls = M_.params(strmatch('c_z_2', M_.param_names, 'exact'));
disp(sprintf('Estimate of e_c_m: %f', e_c_m_nls))
disp(sprintf('Estimate of c_z_1: %f', c_z_1_nls))
disp(sprintf('Estimate of c_z_2: %f', c_z_2_nls))

8
tests/pac/var-8e/example1.mod
View File

@ -84,11 +84,3 @@ eparams.c_z_2 = .2;
edata = TrueData;
edata.ez = dseries(NaN(TrueData.nobs, 1), 2000Q1, 'ez');
pac.estimate.nls('zpac', eparams, edata, 2005Q1:2005Q1+4000, 'fmincon');
e_c_m_nls = M_.params(strmatch('e_c_m', M_.param_names, 'exact'));
c_z_1_nls = M_.params(strmatch('c_z_1', M_.param_names, 'exact'));
c_z_2_nls = M_.params(strmatch('c_z_2', M_.param_names, 'exact'));
disp(sprintf('Estimate of e_c_m: %f', e_c_m_nls))
disp(sprintf('Estimate of c_z_1: %f', c_z_1_nls))
disp(sprintf('Estimate of c_z_2: %f', c_z_2_nls))

8
tests/pac/var-9e/example1.mod
View File

@ -88,11 +88,3 @@ eparams.c_z_2 = .2;
edata = TrueData;
edata.ez = dseries(NaN(TrueData.nobs, 1), 2000Q1, 'ez');
pac.estimate.nls('zpac', eparams, edata, 2005Q1:2005Q1+4000, 'fmincon');
e_c_m_nls = M_.params(strmatch('e_c_m', M_.param_names, 'exact'));
c_z_1_nls = M_.params(strmatch('c_z_1', M_.param_names, 'exact'));
c_z_2_nls = M_.params(strmatch('c_z_2', M_.param_names, 'exact'));
disp(sprintf('Estimate of e_c_m: %f', e_c_m_nls))
disp(sprintf('Estimate of c_z_1: %f', c_z_1_nls))
disp(sprintf('Estimate of c_z_2: %f', c_z_2_nls))