I want to model each state to have a group level slope on
day, and want these slopes to come from a common distribution
f = bf(y ~ (1 | state) + (0 + day | state)) m <- brm(f, df, prior = c( prior(normal(0, 2), class = b) ), cores = 4, control = list(adapt_delta = .995))
which throws an error
Error: The following priors do not correspond to any model parameter: b ~ normal(0, 2) Function 'get_prior' might be helpful to you.
> get_prior(f, data = df) prior class coef group resp dpar nlpar bound 1 student_t(3, 1, 10) Intercept 2 student_t(3, 0, 10) sd 3 sd state 4 sd day state 5 sd Intercept state 6 student_t(3, 0, 10) sigma
How can I specify the prior for group-level slopes?