I want to extract the estimated parameters from distributional models via Bayesian model stacking. I am using pp_average to calculate the posterior predictive values averaged across models. But it seems that I can only get the predicted values for y rather than sigma from the stacked model. The simplified model is attached below.
y ~ x1 sigma ~ x1
y ~ x2 sigma ~ x2
pp_average(model1, model2, weights = 'stacking')
I am wondering whether it is also possible to get the predicted values for sigma, and extract the estimated parameters for x1 and x2 from the stacked model in brms. Thanks a lot!