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lines 18-97 of file: devel/cmd/predict_command.cpp
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{xrst_begin predict_command}

The Predict Command
###################

Syntax
******
``dismod_at`` *database* ``predict`` *source*
``dismod_at`` *database* ``predict`` *source* ``zero_meas_value``

database
********
Is an
`sqlite <https://www.sqlite.org/index.html>`_ database containing the
``dismod_at`` :ref:`input-name` tables which are not modified.

source
******
This argument specifies where model variable values to use
for the predictions. The possible values are listed below:

sample
======
If *source* is ``sample`` ,
the values in the :ref:`sample_table-name` are used for the predictions.
In this case there are
:ref:`simulate_command@number_simulate` sets
of model variables that predictions are computed for.
If the samples were simulated using the
:ref:`sample_command@asymptotic` method,
they may not be withing the lower and upper limits for the
corresponding variables.
The variables are censored to be within their limits before
the predictions are computed.

fit_var
=======
If *source* is ``fit_var`` ,
the values in the :ref:`fit_var_table-name` are used for the predictions.
In this case there is only one set of model variables that the
predictions are computed for and
:ref:`predict_table@sample_index` is always zero.

truth_var
=========
If *source* is ``truth_var`` ,
the values in the :ref:`truth_var_table-name` are used for the predictions.
In this case there is only one set of model variables that the
predictions are computed for and
:ref:`predict_table@sample_index` is always zero.

zero_meas_value
***************
If this argument is present, the value zero is used for the
:ref:`mulcov_table@mulcov_type@meas_value` covariate multipliers
(instead of the value in the *source* table).
This predicts what the mean of the corresponding data
would be if there were no measurement value covariate effects.


predict_table
*************
A new :ref:`predict_table-name` is created each time this command is run.
It contains the
:ref:`average integrand<avg_integrand@Average Integrand, A_i>`
values for set of model variables
and each
:ref:`predict_table@avgint_id`
in the
:ref:`predict_table@Avgint Subset` .
{xrst_toc_hidden
   example/get_started/predict_command.py
}
Example
*******
The files :ref:`predict_command.py-name` and
:ref:`user_predict_fit.py-name` contain examples and tests
using this command.

{xrst_end predict_command}