I am using cmdstanr, and I have a code that creates some transformed parameters, the problem is that these transformed parameters are very big vector >3k samples and I have multiple like this, so a total of more than 12k different transformed parameters. Once the model finishes I when I want to get the summary or draws it is very slow and inconvenient, either by using posterior or shinystan, also these are parameters that I don’t need so they are also a waste of space, is there a way to remove them from the fitted output. I don’t care about them, they are just an intermediate output, so maybe the .stan needs to be written differently? As an example this is how the model is written

```
data{
// the initial data is only used to transform it, not in the final model
vector[N] values;
}
parameters{
real k;
real beta;
}
transformed parameters{
// create the transformed values by using a function and a parameter to tune
vector[N] values_tf = fn(values, k)
}
model{
target ~ normal(values_tf * beta)
}
```

Thanks