default_prior: Default priors for Bayesian models

In paul-buerkner/brms: Bayesian Regression Models using 'Stan'

Default priors for Bayesian models

Description

default_prior is a generic function that can be used to get default priors for Bayesian models. Its original use is within the brms package, but new methods for use with objects from other packages can be registered to the same generic.

Usage

default_prior(object, ...)

get_prior(formula, ...)

Arguments

object	An object whose class will determine which method will be used. A symbolic description of the model to be fitted.
...	Further arguments passed to the specific method.
formula	Synonym of object for use in get_prior.

Details

See default_prior.default for the default method applied for brms models. You can view the available methods by typing methods(default_prior).

Value

Usually, a brmsprior object. See default_prior.default for more details.

See Also

set_prior, default_prior.default

Examples

## get all parameters and parameters classes to define priors on
(prior <- default_prior(count ~ zAge + zBase * Trt + (1|patient) + (1|obs),
                        data = epilepsy, family = poisson()))

paul-buerkner/brms documentation built on April 14, 2024, 5:39 p.m.