I am playing around with using BART to predict horse speed (y_pred) using some old horse racing data. Here is my model:

```
with pm.Model() as model_jockey:
X = pm.MutableData("X",x_train)
Y = y_data
mu = pmb.BART("mu", X=X, Y=Y, m=10) ## up this to at least ?100? for production
sigma = pm.HalfNormal("sigma",sigma=0.25)
y_pred = pm.StudentT("y_pred", mu=mu, sigma=sigma, nu=2, observed=Y, shape = X.shape[0])
idata_jockey = pm.sample(random_seed=RANDOM_SEED) #, initvals = initial_values)
```

I am able to predict `y_pred`

for out of sample data using this code:

```
with model_jockey:
pm.set_data({"X": x_test})
ppc2 = pm.sample_posterior_predictive(
trace=idata_jockey, random_seed=RANDOM_SEED,
extend_inferencedata=True, predictions = True
)
```

But for the life of me, I cannot figure out how get out-of-sample predictions for “mu”. How can I get the “mu” values used to sample from the posterior predictive when generating the y_pred values in the PPC?