Hello!

Grateful for any assistance here… I might just be being daft and not seeing what’s going on.

The WAIC and LOO give an estimate of elppd, the expected log pointwise predictive density for a new dataset.

Suppose that I have a normal observation model, ie

`y[i] ~ normal(pred[i], sigma)`

for the `i`

th data point and `pred[i]`

is the model prediction for the `i`

th data point.

Is there a simple relationship between either WAIC or LOO, or elppd_WAIC or elppd_LOO, and the expected mean squared error (MSE) on a new data set?

I’m trying to communicate my findings to a non-technical audience and expected MSE on new data is much better understood by them. My model is quite expensive to compute so I’m trying to avoid doing explicit cross-validation.

Thanks in advance!