R: Overview on Priors for 'brms' Models

get_prior {brms} | R Documentation

## Overview on Priors for brms Models

### Description

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

### Usage

    get_prior(formula, data, family = gaussian(), autocor = NULL,
      internal = FALSE)

### Arguments

`formula` | An object of class `formula`, `brmsformula`, or `mvbrmsformula` (or one that can be coerced to that classes): A symbolic description of the model to be fitted. The details of model specification are explained in `brmsformula`.
`data` | An object of class `data.frame` (or one that can be coerced to that class) containing data of all variables used in the model.
`family` | A description of the response 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. Every family function has a `link` argument allowing to specify the link function to be applied on the response variable. If not specified, default links are used. For details of supported families see `brmsfamily`. By default, a linear `gaussian` model is applied. In multivariate models, `family` might also be a list of families.
`autocor` | An optional `cor_brms` object describing the correlation structure within the response variable (i.e., the 'autocorrelation'). See the documentation of `cor_brms` for a description of the available correlation structures. Defaults to `NULL`, corresponding to no correlations. In multivariate models, `autocor` might also be a list of autocorrelation structures.
`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 parameter (or parameter class) on which priors can be specified. The prior column is empty except for internal default priors.

### See Also

`set_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 population-level effects a once
    prior$prior[1] <- "normal(0,10)"

    ## define a specific prior on the population-level 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)

[Package brms version 2.6.0 Index]