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Allow hierarchical or no pooling of trend components

Open nicholasjclark opened this issue 1 year ago • 1 comments

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

nicholasjclark avatar Nov 17 '23 05:11 nicholasjclark

If this goes ahead it'll undoubtedly need the noncentred parameterisation

nicholasjclark avatar Apr 11 '24 19:04 nicholasjclark