Dear users,

I would like to know if Jacobian adjustment is required for the following situation.

my model has parameters whose “typical” values are either very small and very large. Following through Stans manual about prior choice, https://github.com/stan-dev/stan/wiki/Prior-Choice-Recommendations, what I have been doing is to convert both large and small parameters on a unit scale. For example, if the typical value of beta is 3.8x10^-10, and the typical value of eta is 20000, then these are changed into

```
beta_raw = log(beta/3.8x10^-10) and
eta_raw = log(eta/20000)
```

In Stan code these are coded as

```
parameters{
real beta_raw;
real eta_raw;
}
transformed parameters{
real<lower = 0> beta;
real<lower = 0> eta;
beta = exp(beta_raw)*3.8e-10;
eta = exp(eta_raw)*2e4;
}
model{
beta_raw ~ normal(0, 1);
eta_raw ~ normal(0,1);
}
```

My question is do I need to include Jacobian adjustment for beta_raw and eta_raw?

Reading through Stan’s documentation about **Change of variables and reparametrisations** , http://mc-stan.org/docs/bayes-stats-stan/change-of-variables-chapter.html, I could not figure out when to use Jacobian adjustment or when to not use it.

Thanks