In my Stan model, I fixed one parameter to zero to satisfy some identifiability constraints.

When I sample, I obtained the desired sampling but I obtain warning messages that the largest Rhat is NA because of the fixed parameter.

```
Warning messages:
1: The largest R-hat is NA, indicating chains have not mixed.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#r-hat
2: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#bulk-ess
3: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
Running the chains for more iterations may help. See
http://mc-stan.org/misc/warnings.html#tail-ess
```

```
mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat valid Q5 Q50 Q95 MCSE_Q2.5 MCSE_Q25 MCSE_Q50 MCSE_Q75 MCSE_Q97.5 MCSE_SD Bulk_ESS
k[1] 0 0 0 0 0 0 0 0 NA 1 1 0 0 0 NA NA NA NA NA NA 4000
Tail_ESS
k[1] 4000
```

In the forum, I saw some â€śtricksâ€ť to avoid this message, for example:

- Include the rstan sampling call in
`suppressWarnings()`

. This will indeed suppress warnings but might suppress also other important warnings as well. - Include the parameter constraint in the
`model`

block instead of the`transformed parameters`

block. That would indeed work but I would like to keep the constrained parameter in the set of my parameters.

My general question is then: is it possible to fix one parameter in the parameter space without having this â€śfalseâ€ť warning?

Thank you for your help!