12 Standalone Generate Quantities
The generate_quantities
method allows you to generate additional
quantities of interest from a fitted model without re-running the sampler.
For an overview of the uses of this feature, see the
QuickStart Guide section
and the Stan User’s Guide section on
Stand-alone generated quantities and ongoing prediction.
This method requires sub-argument fitted_params
which takes as its value
an existing Stan CSV file that contains a sample from an equivalent model,
i.e., a model with the same parameters, transformed parameters, and model blocks,
conditioned on the same data.
If we run the bernoulli.stan
program for a single chain to
generate a sample in file bernoulli_fit.csv
:
> ./bernoulli sample data file=bernoulli.data.json output file=bernoulli_fit.csv
Then we can run the bernoulli_ppc.stan
to carry out the posterior predictive
checks:
> ./bernoulli_ppc generate_quantities fitted_params=bernoulli_fit.csv \
data file=bernoulli.data.json \
output file=bernoulli_ppc.csv
The fitted_params
file must be a Stan CSV file; attempts to use a regular CSV file
will result an error message of the form:
Error reading fitted param names from sample csv file <filename.csv>
The fitted_params
file must contain columns corresponding to legal values
for all parameters defined in the model.
If any parameters are missing, the program will exit with an error
message of the form:
Error reading fitted param names from sample csv file <filename.csv>
The parameter values of the fitted_params
are on the
constrained scale and must obey all constraints.
For example, if we modify the contencts of the first
reported draw in bernoulli_fit.csv
so that the value
of theta
is outside the declared bounds real<lower=0,upper=1>
,
the program will return the following error message:
Exception: lub_free: Bounded variable is 1.21397, but must be in the interval [0, 1] (in 'bernoulli_ppc.stan', line 5, column 2 to column 30)