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Removed lgyidx2varobs field (vector of integers) in options_. Added checks about the declared observed variables.

time-shift
Stéphane Adjemian (Charybdis) 2013-09-09 13:57:34 +02:00
parent c824217163
commit 7756bc3af2
2 changed files with 27 additions and 7 deletions
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29
matlab/dynare_estimation_init.m
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@ -49,16 +49,35 @@ else
options_.varlist = var_list_;
end
% Get the indices of the observed variables in M_.endo_names.
options_.lgyidx2varobs = zeros(size(M_.endo_names,1),1);
for i = 1:size(M_.endo_names,1)
% Set the number of observed variables.
options_.number_of_observed_variables = length(options_.varobs);
% Check that each declared observed variable is also an endogenous variable.
for i = 1:options_.number_of_observed_variables
id = strmatch(options_.varobs{i}, M_.endo_names, 'exact');
if isempty(id)
error(['Unknown variable (' options_.varobs{i} ')!'])
end
end
% Check that a variable is not declared as observed more than once.
if ~isequal(varobs,unique(varobs))
for i = 1:options_.number_of_observed_variables
if length(strmatch(varobs{i},varobs))>1
error(['A variable cannot be declared as observed more than once (' options_.varobs{i} ')!'])
end
end
end
for i = 1:M_.endo_nbr
tmp = strmatch(deblank(M_.endo_names(i,:)),options_.varobs,'exact');
if ~isempty(tmp)
if isempty(tmp)
error(['Multiple declarations of ' deblank(M_.endo_names(i,:)) ' as an observed variable is not allowed!'])
else
if length(tmp)>1
skipline()
error(['Multiple declarations of ' deblank(M_.endo_names(i,:)) ' as an observed variable is not allowed!'])
end
options_.lgyidx2varobs(i) = tmp;
end
end

5
matlab/particle/solve_model_for_online_filter.m
View File

@ -201,9 +201,10 @@ end
% Get the off-diagonal elements of the covariance matrix for the measurement errors. Test if H is positive definite.
if EstimatedParameters.ncn
corrn_observable_correspondence = EstimatedParameters.corrn_observable_correspondence;
for i=1:EstimatedParameters.ncn
k1 = DynareOptions.lgyidx2varobs(EstimatedParameters.corrn(i,1));
k2 = DynareOptions.lgyidx2varobs(EstimatedParameters.corrn(i,2));
k1 = corrn_observable_correspondence(i,1);
k2 = corrn_observable_correspondence(i,2);
H(k1,k2) = xparam1(i+offset)*sqrt(H(k1,k1)*H(k2,k2));
H(k2,k1) = H(k1,k2);
end