I would like to better understand how to manually initialise a `pymc.fit`

when using `method='advi'`

.

Specifically I am using

```
advi = pymc.ADVI()
tracker = pymc.variational.callbacks.Tracker(
mean = advi.approx.mean.eval,
std = advi.approx.std.eval,
)
```

in order to ‘track’ the parameters (are those ‘model parameters’ or the ADVI parameters \mu and \rho?) of the fit.

How can I use `tracker["mean"]`

and `tracker["std"]`

as `start`

and `start_std`

of `pymc.fit`

? Does that even make sense?

In How to initialize ADVI it is suggested to use the posterior mean of the *model parameters* to initialize the fit. I would have expected that I need to supply starting parameters for \mu and \rho instead?

Arguments `start`

and `start_std`

require a dictionary but `tracker["mean"][-1]`

is an array, i.e. I am missing the correct keys, unless I really need to specify the *model parameters*. In that case should I use the posterior standard deviation to initialise `start_std`

?

So essentially I am confused as to which parameters I need to supply for the initialisation? The one of the model or the one of the ADVI (mean field) approximation? And if I need to specify the parameters for the approximation, `\mu`

and `\rho`

, which are the correct keys for the `start`

and `start_std`

dictionaries?