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Use makedataset in condition forecast routine.

time-shift
Stéphane Adjemian (Scylla) 2014-06-26 10:55:54 +02:00
parent 03395a7425
commit 62e28dac94
1 changed files with 5 additions and 23 deletions
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28
matlab/imcforecast.m
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@ -102,30 +102,13 @@ if estimated_model
error('imcforecast:: The dimension of the vector of parameters doesn''t match the number of estimated parameters!')
end
end
set_parameters(xparam);
% Load and transform data.
transformation = [];
if options_.loglinear && ~options_.logdata
transformation = @log;
end
xls.sheet = options_.xls_sheet;
xls.range = options_.xls_range;
if ~isfield(options_,'nobs')
options_.nobs = [];
end
dataset_ = initialize_dataset(options_.datafile,options_.varobs,options_.first_obs,options_.nobs,transformation,options_.prefilter,xls);
data = dataset_.data;
data_index = dataset_.missing.aindex;
gend = options_.nobs;
missing_value = dataset_.missing.state;
[dataset_,dataset_info] = makedataset(options_);
data = transpose(dataset_.data);
data_index = dataset_info.missing.aindex;
gend = dataset_.nobs;
missing_value = dataset_info.missing.state;
[atT,innov,measurement_error,filtered_state_vector,ys,trend_coeff] = DsgeSmoother(xparam,gend,data,data_index,missing_value);
trend = repmat(ys,1,options_cond_fcst.periods+1);
for i=1:M_.endo_nbr
j = strmatch(deblank(M_.endo_names(i,:)),options_.varobs,'exact');
@ -134,7 +117,6 @@ if estimated_model
end
end
trend = trend(oo_.dr.order_var,:);
InitState(:,1) = atT(:,end);
else
InitState(:,1) = zeros(M_.endo_nbr,1);