# get_prior

0th

Percentile

##### Overview on Priors for brms Models

Get information on all parameters (and parameter classes) for which priors may be specified including default priors.

##### Usage
get_prior(formula, data = NULL, family = gaussian(), autocor = NULL,
partial = NULL, threshold = c("flexible", "equidistant"),
internal = FALSE)
##### Arguments
formula
An object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under 'Details'.
data
An optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically t
family
A description of the error distribution and link function to be used in the model. This can be a family function, a call to a family function or a character string naming the family. Currently, the following families are supported: gaussian
autocor
An optional cor_brms object describing the correlation structure within the response variable (i.e. the 'autocorrelation'). See the documentation of cor_brms
partial
A one sided formula of the form ~expression allowing to specify predictors with category specific effects in non-cumulative ordinal models (i.e. in families cratio, sratio, or acat).
threshold
A character string indicating the type of thresholds (i.e. intercepts) used in an ordinal model. "flexible" provides the standard unstructured thresholds and "equidistant" restricts the distance between consecutive thresh
internal
A flag indicating if the names of additional internal parameters should be displayed. Setting priors on these parameters is not recommended
##### Value

• A data.frame with columns prior, class, coef, and group and several rows, each providing information on a paramter (or parameter class) on which priors can be specified. The prior column is empty except for internal default priors.

set_prior

• get_prior
##### Examples
## get all parameters and parameters classes to define priors on
(prior <- get_prior(count ~ log_Age_c + log_Base4_c * Trt_c
+ (1|patient) + (1|visit),
data = epilepsy, family = poisson()))

## define a prior on all fixed effects a once
prior$prior[1] <- "normal(0,10)" ## define a specific prior on the fixed effect of Trt_c prior$prior[5] <- "student_t(10, 0, 5)"

## verify that the priors indeed found their way into Stan's model code
make_stancode(count ~ log_Age_c + log_Base4_c * Trt_c
+ (1|patient) + (1|visit),
data = epilepsy, family = poisson(),
prior = prior)
Documentation reproduced from package brms, version 0.7.0, License: GPL (>= 3)

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