hi!

I’m fitting the following with the `von mises`

as likelihood function:

```
form_ri_int <- bf(diff_theta ~ 0 + Intercept + emotion * mask + (1|id),
kappa ~ 0 + Intercept + emotion * mask + (1|id))
prior_von_mises <- c(
prior(normal(0, 2), class = "b", dpar = ""), # betas prior
prior(normal(0, 1.5), class = "b", dpar = "kappa") # kappa prior
)
fit_ri_int <- brm(form_ri_int,
data = dat_fit,
prior = prior_von_mises,
family = von_mises(link = "tan_half", link_kappa = "log"),
chains = 15,
cores = 15,
iter = 10000,
file = "theta/fit_ri_int",
seed = seed)
```

Where `diff_theta`

is a variable measured in *radians* of which I’m predicting the circular mean and the spread (kappa).

I have some doubt about interpreting kappa given the link function. I’ve extracted my posterior draws for each parameters that I need and the doing `exp(kappa)`

otherwise some parameters can have negative values. Now the interpretation is that values around 0 means that the distribution is close to uniform and large values means less spread right?