Dear all,

i’m trying to some latent noise within a choice model. More precisely, a classical choice model will be as follows:

```
model{
EV[t] = ... // some function of the data and parameters
choice[t] ~ categorical_logit(EV[t])
}
```

I would like instead something like:

```
model{
mean_EV[t] = ... // some some function of the data and parameters
sigma_EV[t] = ... /// some function of the data and parameters
EV[t] ~ normal(mean_EV[t], sigma_EV[t]);
choice[t] ~ categorical_logit(EV[t])
}
```

This, however, does not work. I realise that the problem is that choice[t] (data) is observed, while EV[t] is not (it’s a latent variable), and therefore that the above “model” is inappropriate. But i cannot figure out how i should code that.

Any help would be great.