First post here, and a newbie to this space. Apologies up front for what are likely elementary questions. Would appreciate your input.
I am using brms & rstan to create models that are estimating a response variable using 1 continuous predictor. There is one grouping variable for random effects (both random intercepts & slopes).
I used the brms::get_prior call to evaluate the priors being used, and I was surprised to see a beta class that was separate from the “Intercept” class.
Can someone clarify the difference between the beta and Intercept classes in the get_priors function? (Screenshot below). Why is the intercept a separate class, given this is a population-level effect?
- Why does sigma (the residual SD) have a student t distribution even when using the gaussian family distribution?
Thanks in advance.