mvgam
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Allow hierarchical or no pooling of trend components
Right now autoregressive and trend variance parameters are 'hierarchical', but the hyperparameters are are fixed (i.e. ar1 ~ normal(0, 0.5)
). It would be useful to allow options to learn these hierarchically, i.e.
ar1 ~ normal(ar1mu, ar1sigma);
ar1mu ~ normal(0.5, 0.1);
ar1sigma ~ exponential(5);
This is probably more relevant for variance parameters as different series may have wildly different dynamics
If this goes ahead it'll undoubtedly need the noncentred parameterisation