Thanks - the issue is that I am trying to run leave-one-group-out cross validation on two nested models and then calculate their stacking weights.
I got somewhat confused by the documentation, because it says:
`` We can use approximate or exact leave-one-out cross-validation (LOO-CV) or K-fold CV to estimate the expected log predictive density (ELPD).
But the function loo_model_weights doesn’t seem to have any parameters that allow you to specify “leave-one-group-out cv” .
I suppose a simpler (I hope) question is, if I have calculated “leave one group out cv” for two nested models:
md1LOGO = kfold(model1, group = “Subject”)
md2LOGO = kold(model2,group = “Subject”)
how do I calculate their stacking weights?