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predict_command¶
View page sourceThe Predict Command¶
Syntax¶
dismod_at database predict source
dismod_at database predict source zero_meas_value
database¶
Is an
sqlite database containing the
dismod_at input 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 sample_table are used for the predictions.
In this case there are
number_simulate sets
of model variables that predictions are computed for.
If the samples were simulated using the
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 fit_var_table are used for the predictions.
In this case there is only one set of model variables that the
predictions are computed for and
sample_index is always zero.
truth_var¶
If source is truth_var ,
the values in the truth_var_table are used for the predictions.
In this case there is only one set of model variables that the
predictions are computed for and
sample_index is always zero.
zero_meas_value¶
If this argument is present, the value zero is used for the 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 predict_table is created each time this command is run. It contains the average integrand values for set of model variables and each avgint_id in the Avgint Subset .
Example¶
The files predict_command.py and user_predict_fit.py contain examples and tests using this command.