Hello,

‘The estimated number of effective samples is smaller than 200 for some parameters.’ notification appears when I conduct NUTS sampler. I tried to change ‘mu’ and ‘sd’ values in order to solve the issue, but the output values are highly effected by them.

I looked for previous related topics, however couldn’t find a solution. What could be the possible reason and consequences of it?

```
with pm.Model() as cohen:
# response
μ0 = pm.Normal('μ0', mu=0, sd=10, shape=groups)
σ0 = pm.HalfNormal('σ0', sd=10, shape=groups)
y0 = pm.Normal('y0', mu=μ0[idx], sd=σ0[idx], observed=rsp)
# reaction time
μ1 = pm.Normal('μ1', mu=0, sd=10, shape=groups)
σ1 = pm.HalfNormal('σ1', sd=10, shape=groups)
y1 = pm.Normal('y1', mu=μ1[idx], sd=σ1[idx], observed=rt)
trace_cohen = pm.sample(target_accept=0.99)
```

```
Auto-assigning NUTS sampler...
Initializing NUTS using jitter+adapt_diag...
Multiprocess sampling (4 chains in 4 jobs)
NUTS: [σ1, μ1, σ0, μ0]
Sampling 4 chains, 0 divergences: 100%|████████████████████████████████████████| 4000/4000 [00:27<00:00, 143.73draws/s]
The estimated number of effective samples is smaller than 200 for some parameters.
```