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Manual: document more precisely the column (resp. row) indices of oo_.endo_simul (resp. oo_.exo_simul) 

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Sébastien Villemot 2023-02-16 17:06:04 -05:00
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doc/manual/source/the-model-file.rst
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@ -3851,8 +3851,10 @@ speed-up on large models.
periods option or by ``extended_path``). The variables are periods option or by ``extended_path``). The variables are
arranged row by row, in order of declaration (as in arranged row by row, in order of declaration (as in
``M_.endo_names``). Note that this variable also contains initial ``M_.endo_names``). Note that this variable also contains initial
and terminal conditions, so it has more columns than the value of and terminal conditions, so it has more columns than the value of the
``periods`` option. ``periods`` option: the first simulation period is in
column ``1+M_.maximum_lag``, and the total number of columns is
``M_.maximum_lag+periods+M_.maximum_lead``.
.. matvar:: oo_.exo_simul .. matvar:: oo_.exo_simul
@ -3862,7 +3864,25 @@ speed-up on large models.
in columns, in order of declaration (as in in columns, in order of declaration (as in
``M_.exo_names``). Periods are in rows. Note that this convention ``M_.exo_names``). Periods are in rows. Note that this convention
regarding columns and rows is the opposite of the convention for regarding columns and rows is the opposite of the convention for
``oo_.endo_simul``! ``oo_.endo_simul``! Also note that this variable also contains initial
and terminal conditions, so it has more rows than the value of the
``periods`` option: the first simulation period is in row
``1+M_.maximum_lag``, and the total number of rows is
``M_.maximum_lag+periods+M_.maximum_lead``.
.. matvar:: M_.maximum_lag
|br| The maximum number of lags in the model. Note that this value is
computed on the model *after* the transformations related to auxiliary
variables, so in practice it is either 1 or 0 (the latter value corresponds
to a purely forward or static model).
.. matvar:: M_.maximum_lead
|br| The maximum number of leads in the model. Note that this value is
computed on the model *after* the transformations related to auxiliary
variables, so in practice it is either 1 or 0 (the latter value corresponds
to a purely backward or static model).
Perfect foresight with expectation errors Perfect foresight with expectation errors
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