brms (version 2.7.0)

stanvar: User-defined variables passed to Stan

Description

Prepare user-defined variables to be passed to one of Stan's program blocks. This is primarily useful for defining more complex priors, for refitting models without recompilation despite changing priors, or for defining custom Stan functions.

Usage

stanvar(x = NULL, name = NULL, scode = NULL, block = "data")

Arguments

x

An R object containing data to be passed to Stan. Only required if block = 'data' and ignored otherwise.

name

Optinal character string providing the desired variable name of the object in x. If NULL (the default) the variable name is directly infered from x.

scode

Line of Stan code to define the variable in Stan language. If block = 'data', the Stan code is inferred based on the class of x by default.

block

Name of one of Stan's program blocks in which the variable should be defined. Can be 'data', 'tdata' (transformed data), 'parameters', 'tparameters' (transformed parameters), 'model', 'genquant' (generated quantities) or 'functions'.

Value

An object of class stanvars.

Examples

# NOT RUN {
bprior <- prior(normal(mean_intercept, 10), class = "Intercept")
stanvars <- stanvar(5, name = "mean_intercept")
make_stancode(count ~ Trt, epilepsy, prior = bprior, 
              stanvars = stanvars)
              
# define a multi-normal prior with known covariance matrix
bprior <- prior(multi_normal(M, V), class = "b")
stanvars <- stanvar(rep(0, 2), "M", scode = "  vector[K] M;") +
  stanvar(diag(2), "V", scode = "  matrix[K, K] V;") 
make_stancode(count ~ Trt + log_Base4_c, epilepsy,
              prior = bprior, stanvars = stanvars)
              
# define a hierachical prior on the regression coefficients
bprior <- set_prior("normal(0, tau)", class = "b") +
  set_prior("target += normal_lpdf(tau | 0, 10)", check = FALSE)
stanvars <- stanvar(scode = "real<lower=0> tau;", 
                    block = "parameters")
make_stancode(count ~ Trt + log_Base4_c, epilepsy,
              prior = bprior, stanvars = stanvars)

# }