I want to model each state to have a group level slope on `day`

, and want these slopes to come from a common distribution

I tried

```
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.
```

This gives

```
> 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?