Hello,

given a Turing model

```
@model function λ(y)
λ₁ ~ Exponential(alpha)
for i in 1:length(y)
y[i] ~ Poisson(λ₁)
end
end
```

what is the meaning of the y array?

I think it is used to compute the posterior.

When I call a sampler, y will be the data. So in the model strucutre the data is rewrite by the distribution?

**Question 0: How does it works exactly?**

**Question 1: How can I plot the y distribution?**

Calling plot(sample(myModel(data), sampler(), n)) does not plot y.

Using PyMC3 the posterior distribution can be plotted as described here:

(figure at “4. Plot the artificial dataset:”)

**Question 2: Can I use map/broadcast instead of**

```
for i in 1:length(y)
y[i] ~ Poisson(λ₁)
end
```

?