I’m trying to optimize a hierarchical model that requires some parameters to be bounded at lower=0.5, upper=1.

It runs with a centered cholesky factored parametrization, but the participant-level effects are highly correlated, it samples slowly, and I have lots of divergences.

So I thought I’d try a non-centered parametrization, but I’ve run into a weird error when trying to specify the bounds of the participant-level effects as a function of the main effect.

I’ve managed to isolate the error and create a minimal example (included below).

In this example, the error sometimes doesn’t happen if I don’t specify init=0 (and sometimes it still happens but with different “lb is…” numbers), but it always happens with the real model.

I tried searching around, but didn’t find any mentions of this error message, and I don’t have a clue what’s going on.

**stan**

```
data{
int<lower=1> N;
int<lower=1> P;
int<lower=1, upper=P> participant[N];
}
parameters{
real<lower=0.5, upper=1> muA;
vector<lower=muA-.5, upper=1-muA>[P] a;
}
transformed parameters {
vector<lower=0.5, upper=1>[N] total_A;
total_A = (muA + a[participant]);
}
model{
muA ~ normal(0, 1);
a ~ normal(0, 1);
}
```

**R**

```
library(rstan)
data = list(
N = 10,
P = 5,
participant = c(1:5, 1:5)
)
debug_model <- stan(
file = "stan_debug_lub.stan",
data = data,
iter = 1e5, chains = 1, cores = 1, init=0
)
```

**The error**

```
[1] "Error in sampler$call_sampler(args_list[[i]]) : "
[2] " lub_constrain: lb is 0.25, but must be less than 0.25"
```

Thanks,