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nicholasjclark / mvgam

{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
https://nicholasjclark.github.io/mvgam/
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Multiplicative effects #33

Closed nicholasjclark closed 1 month ago

nicholasjclark commented 7 months ago

Many time series show multiplicative effects, such as seasonality that changes as the underlying level changes. These are easily captured in GAMs using a tensor product (i.e. te(time, season)), but this strategy suffers from poor extrapolations of the marginal time basis. For identity links (gaussian, lognormal, student-t), it may be useful to allow effects to be multiplied by the trend estimate

nicholasjclark commented 1 month ago

Not needed now that we can use the Random Walk basis from MRFtools. Closing as this isn't a priority