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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)