Extract Priors of a Bayesian Model Fitted with brms
# S3 method for brmsfit
prior_summary(object, all = TRUE, ...)
For brmsfit
objects, an object of class brmsprior
.
An object of class brmsfit
.
Logical; Show all parameters in the model which may have
priors (TRUE
) or only those with proper priors (FALSE
)?
Further arguments passed to or from other methods.
if (FALSE) {
fit <- brm(count ~ zAge + zBase * Trt
+ (1|patient) + (1|obs),
data = epilepsy, family = poisson(),
prior = c(prior(student_t(5,0,10), class = b),
prior(cauchy(0,2), class = sd)))
prior_summary(fit)
prior_summary(fit, all = FALSE)
print(prior_summary(fit, all = FALSE), show_df = FALSE)
}
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