Fit a brms model with count data
fit_brms_binomial(
.formula,
.data,
verbose = TRUE,
.prior = c(prior_string("normal(0, 1)", class = "b"), prior_string("normal(0, 1)",
class = "sd"), prior_string("normal(0, 1)", class = "Intercept")),
.iter = 2000,
.warmup = floor(.iter/2),
.cores = 4,
.chains = 4,
.backend = "rstan",
.seed = 2138
)
model specification
collapsed survey dataset, built from ccesMRPprep::build_counts
Whether to show iteration messages
prior specification that can be interpreted by brms. The default is a standard normal prior, which is tighter than the brms default but has shown to have good prior posterior draws
Number of total iterations.
Of the iterations, how much are burn-ins. Defaults to half.
Number of cores to uses
Number of chains to pass on fit_brms
The backend argument of brms. Defaults to "rstan"
, can also
be "cmdstanr"
seed for randomization to pass into brm