Short summary of the problem

I would like to know how to calculate the phylogenetic signal for models with varying slopes and intercepts. Following from https://cran.r-project.org/web/packages/brms/vignettes/brms_phylogenetics.html

If I have a Phylogenetic Model with repeated Measurements, but also with varying slopes (below), how does it affect the formula for `hypothesis()`

given in the original example?

```
model_repeat1 <- brm(
phen ~ cofactor1*cofactor2 + (1|gr(phylo, cov = A)) + (1+cofactor1+cofactor2|species),
data = data_repeat,
family = gaussian(),
data2 = list(A = A),
prior = c(
prior(normal(0,10), "b"),
prior(normal(0,50), "Intercept"),
prior(student_t(3,0,20), "sd"),
prior(student_t(3,0,20), "sigma")
),
sample_prior = TRUE, chains = 2, cores = 2,
iter = 4000, warmup = 1000
)
```

Thanks

- Operating System: Windows 11 (64-bit operating system)
- brms Version: 2.20.1