stan

Classes

Functions

make_stancode(formula, data, priors=None, family='poisson', sample_prior='no', formula_args=None)

Generate Stan code using brms::make_stancode().

Useful for inspecting the generated Stan model before fitting, understanding the model structure, or using the code with other Stan interfaces.

Parameters:

Name	Type	Description	Default
formula	str or FormulaResult	brms formula specification	required
data	DataFrame	Model data	required
priors	list of PriorSpec	Prior specifications from prior() function	None
family	str	Distribution family (gaussian, poisson, binomial, etc.)	"poisson"
sample_prior	str	Whether to sample from prior: - "no": No prior samples - "yes": Include prior samples alongside posterior - "only": Sample from prior only (no data)	"no"
formula_args	dict	Additional arguments passed to formula()	None

Returns:

Type	Description
str	Complete Stan program code as string

See Also

brms::make_stancode : R documentation https://paulbuerkner.com/brms/reference/make_stancode.html fit : Fit model instead of just generating code make_standata : Generate Stan data block

Examples:

Generate Stan code for simple model:

from brmspy import brms
epilepsy = brms.get_brms_data("epilepsy")

stan_code = brms.make_stancode(
    formula="count ~ zAge + zBase * Trt + (1|patient)",
    data=epilepsy,
    family="poisson"
)

print(stan_code[:500])  # Print first 500 characters

With custom priors:

    from brmspy import prior

    stan_code = brms.make_stancode(
        formula="count ~ zAge",
        data=epilepsy,
        priors=[prior("normal(0, 1)", class_="b")],
        family="poisson"
    )

For prior predictive checks (sample_prior="only"):

stan_code = brms.make_stancode(
    formula="count ~ zAge",
    data=epilepsy,
    family="poisson",
    sample_prior="only"
)