cb4384bb27
The routine takes a dseries object as unique argument and return an updated object with the expectation term. If the mod file is named `example.mod` and if the (VAR/PAC) expectation model is named `toto`, then after var_expectation.print('toto'); the expectation term can be evaluated: ts = example.var_expectations.evaluate_varexp(ts); where ts is a dseries object containing all the time series appearign in the auxiliary (var or trend_component). |
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