[This seems like a super obvious FAQ, but I can’t find an answer to it because I have no idea what set of keywords would reveal it.]

How do I represent a multi-variable observation process? I’m not sure of the right term for this, so let’s take an example:

What if when I observe some process, I get *simultaneous* values for variables *A, B* and *C*? Put differently, every observation is of the form *<a, b, c>*?

Is this correctly represented as, for example:

```
Variable("A", observed=as)
Variable("B", observed=bs)
Variable("C", observed=cs)
```

My guess is that the answer is “no”, and the *as, bs,* and *cs* above would be taken as independent observations of the three variables.

But in my case, the observations include `(a[0], b[0]. c[0])`

, and so forth and `(a[x],b[y],c[z])`

is an incorrect observation, in general, unless *x = y = z*.

In general, also, *A, B,* and *C* are **not** the same type of variables (e.g., A might be `Categorical`

, B `TruncatedNormal`

, and C `Gamma`

), so I can’t just make a vector with shapes.

As I said, this seems like an incredibly basic question, but I don’t know how to find an explanation of what it means when multiple variables in a model are observed, or how to make a tuple of observations. I can’t build an observation tuple with a deterministic RV, because I can’t observe a deterministic RV.

Thanks, and apologies for such a basic question.