Please also provide the following information in addition to your question:

- Operating System: Ubuntu 18.04
- brms Version: 2.10.5 (from github)

Hello!

I am trying to simulate data from a Structural Equation Model, in order to estimate the number of data points necessary to estimate such a DAG.

However, I am struggling with the prior specification. I try to put priors on each coefficients to represent my current believes… I present there after a minimal reproducible exemple, which is a multivariate model of two variables sharing the same predictors.

Data : DAG_exemple.csv (4.3 KB)

```
form_DAG <- bf(MoussPV ~ Hum + Biom + Hum:Exclos + Biom:Exclos,
family = Gamma(link = "log")) +
bf(SLA ~ Hum + Biom + Hum:Exclos + Biom:Exclos,
family = Gamma(link = "log"))
priors_DAG <- c(
## MoussPV
prior(normal(log(1.2), log(1.2)), coef = Biom, resp = MoussPV),
prior(normal(log(1.2), log(1.2)), coef = Biom:ExclosTemoin, resp = MoussPV),
prior(normal(log(1.2), log(1.2)), coef = Hum, resp = MoussPV),
prior(normal(log(1.2), log(1.2)), coef = Hum:ExclosTemoin, resp = MoussPV),
prior(normal(0.1,0.1), class = Intercept, resp = MoussPV),
## SLA
prior(normal(log(1.2), log(1.2)), coef = Biom, resp = SLA),
prior(normal(log(1.2), log(1.2)), coef = Biom:ExclosTemoin, resp = SLA),
prior(normal(log(1.2), log(1.2)), coef = Hum, resp = SLA),
prior(normal(log(1.2), log(1.2)), coef = Hum:ExclosTemoin, resp = SLA),
prior(normal(0.1,0.1), class = Intercept, resp = SLA)
)
simu <- brm(formula = form_DAG, priors = priors_DAG,
data = D, sample_prior = "only",
iter = 10, chains = 3, cores = 3)
```

The following error message then appears.

```
Erreur : Sampling from priors is not possible as some parameters have no proper priors. Error occured for class 'b_MoussPV'.
```

Am I missing something obvious??

Thank you!

Lucas