Just a quick question:

Suppose I have a multivariate model (to keep it really simple)

\begin{align}
y_1 &\sim \text{Poisson}(\exp(a + b)) \\
y_2 &\sim \text{Poisson}(\exp(a)),
\end{align}

where both a and b are parameters. **How can I restrict a to be the same across equations?**

In brms I think I can do (for y_1)

```
priors1 <- prior(normal(0, 0.25), nlpar = "a") +
prior(normal(0.7, 0.25), nlpar = "b")
bf1 <- bf(y1 ~ a + b, a + b ~ 1, nl = TRUE) + poisson(link = "log")
mod1 <- brm(bf1, data = data, prior = priors1)
```

and for y_2:

```
priors2 <- prior(normal(0, 0.25), nlpar = "a")
bf2 <- bf(y2 ~ a, a ~ 1, nl = TRUE) + poisson(link = "log")
mod2 <- brm(bf2, data = data, prior = priors2)
```

However, I kinda want to do:

```
priors <- prior(normal(0, 0.25), nlpar = "a") +
prior(normal(0.7, 0.25), nlpar = "b")
bf1 <- bf(y1 ~ a + b, a + b ~ 1, nl = TRUE) + poisson(link = "log")
bf2 <- bf(y2 ~ a, a ~ 1, nl = TRUE) + poisson(link = "log")
mod <- brm(bf1 + bf2 + set_rescor(FALSE), data = data, prior = priors1)
```

Where a is the same parameter across equations. Is that possible?

I guess I have to somehow set `resp`

in the `prior`

function?

In Stan code this’d be something like

```
...
parameters{
real a;
real b;
}
model{
y1 ~ poisson_log(a + b);
y2 ~ poisson_log(a);
}
```