In the documentation of mixture model (https://docs.pymc.io/api/distributions/mixture.html)

I saw the following snippet:

What’s the difference between the `sigma`

in `pm.Normal`

and the `sigma`

in `pm.Normal.dist`

?

```
npop = 5
nd = (3, 4)
with pm.Model() as model:
mu = pm.Normal('mu', mu=np.arange(npop), sigma=1, shape=npop) # Each component has an independent mean
w = pm.Dirichlet('w', a=np.ones(npop))
components = pm.Normal.dist(mu=mu, sigma=1, shape=nd + (npop,)) # nd + (npop,) shaped multinomial
like = pm.Mixture('like', w=w, comp_dists = components, observed=data, shape=nd) # The resulting mixture is nd-shaped
```