4 ms·
Can you elaborate a bit? Prophet can use MCMC sampling and includes uncertainty in its forecasts.
by glial 5y ago
Can you elaborate a bit? Prophet can use MCMC sampling and includes uncertainty in its forecasts.
- lr1970 5y agoProphet with MCMC can produce probabilistic forecasts. But how to choose MCMC priors and measure accuracy of the probabilistic forecast are open questions.
- deleted 5y ago[deleted]
- lr1970 5y ago> Can you elaborate a bit? Prophet can use MCMC sampling and includes uncertainty in its forecasts. Prophet is a GAM (Generalised Additive Model). It decomposes time series in additive components: trend, seasonality, holidays and noise. Most interesting time-series are not so simply decomposable. Making Prophet Bayesian and producing probabilistic forecast by MCMC sampling from trend/seasonality/holiday posteriors still keeps its GAM structure. Might be for a simple exploratory analysis Prophet is a good go-to tool but all the research action is now in Deep Learning Forecasting Models. Also, IMHO, Prophet deals with individual TS and teaching it to produce vector forecast for multiple TSes at the same time is tricky (or not even possible).
- glial 5y agoYes, that’s my understanding too. GAMs have structural limitations that harm flexibility and help interpretability. One benefit of Bayesian models that they work with relatively little data - and generally provide greater uncertainty in those cases. Do you happen to know of some DL frameworks that behave similarly? I’m eager to learn.