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)
ith data point and
pred[i] is the model prediction for the
ith 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!