I am building a more complicated model, but have reproduced the warning in a very simple case. The warning does indicate that there is nothing really going wrong, but I don’t like getting that warning - is there anything to be done?

Here is the simple Stan model:

```
data {
int<lower=1> N;
real y[N];
}
parameters {
real mu;
real<lower=0> sigma;
}
model {
mu ~ normal(0, 10);
sigma ~ exponential(1);
y ~ normal(mu, sigma);
}
```

And here is the R code:

```
set.seed(334)
y <- rnorm(30, 10, 3)
N <- length(y)
mod <- cmdstan_model("KSG/simple_normal.stan")
fit <- mod$sample(
data = list(N=N,y=y),
seed = 123,
chains = 4,
parallel_chains = 4,
refresh = 500,
iter_warmup = 500,
iter_sampling = 1000
)
```

And here are the warnings:

```
Running MCMC with 4 parallel chains...
Chain 1 Iteration: 1 / 1500 [ 0%] (Warmup)
Chain 1 Iteration: 500 / 1500 [ 33%] (Warmup)
Chain 1 Iteration: 501 / 1500 [ 33%] (Sampling)
Chain 1 Iteration: 1000 / 1500 [ 66%] (Sampling)
Chain 1 Iteration: 1500 / 1500 [100%] (Sampling)
Chain 2 Iteration: 1 / 1500 [ 0%] (Warmup)
Chain 2 Iteration: 500 / 1500 [ 33%] (Warmup)
Chain 2 Iteration: 501 / 1500 [ 33%] (Sampling)
Chain 2 Iteration: 1000 / 1500 [ 66%] (Sampling)
Chain 2 Iteration: 1500 / 1500 [100%] (Sampling)
Chain 2 Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Chain 2 Exception: normal_lpdf: Scale parameter is 0, but must be > 0! (in '/var/folders/wt/rrrkt68n08b0jrstl_87kpkc0000gn/T/RtmpAna9YA/model-1fc7e1360c5.stan', line 14, column 4 to column 26)
Chain 2 If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
Chain 2 but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Chain 2
Chain 3 Iteration: 1 / 1500 [ 0%] (Warmup)
Chain 3 Iteration: 500 / 1500 [ 33%] (Warmup)
Chain 3 Iteration: 501 / 1500 [ 33%] (Sampling)
Chain 3 Iteration: 1000 / 1500 [ 66%] (Sampling)
Chain 3 Iteration: 1500 / 1500 [100%] (Sampling)
Chain 4 Iteration: 1 / 1500 [ 0%] (Warmup)
Chain 4 Iteration: 500 / 1500 [ 33%] (Warmup)
Chain 4 Iteration: 501 / 1500 [ 33%] (Sampling)
Chain 4 Iteration: 1000 / 1500 [ 66%] (Sampling)
Chain 4 Iteration: 1500 / 1500 [100%] (Sampling)
Chain 1 finished in 0.0 seconds.
Chain 2 finished in 0.0 seconds.
Chain 3 finished in 0.0 seconds.
Chain 4 finished in 0.0 seconds.
All 4 chains finished successfully.
Mean chain execution time: 0.0 seconds.
Total execution time: 0.2 seconds.
```