Comments (3)
An alternative is the "refitted" method, which fits the same ETS model to the data, but with random parameters.
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This is now done via refit() and reforecast() functions for ETS. Things left:
- Stuff for ARIMA,
- Stuff for ETSX / ARIMAX.
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Done for all models via refit() method
from mes.
Related Issues (20)
- Let persistence accept lists HOT 1
- User defined loss functions
- Develop a method to smooth states of the model
- Advanced loss functions to implement HOT 3
- De-bias smoothing parameters in occurrence models
- ETS(NNN)
- Create vignette with basic features of ADAM HOT 1
- Create testthat scripts for ADAM
- Make sure that all combinations of models work
- Deal with parametric prediction interval HOT 1
- Speed up adam with ARIMA HOT 2
- Rewrite regression part of ADAM in the input
- Move adam() to smooth
- ARIMA and ARIMA orders selection on small samples HOT 1
- Outlier detection mechanism HOT 1
- Use Rectified Normal distribution for the summary HOT 2
- Correct distributions in ADAM HOT 1
- Fix the stability condition HOT 1
- xreg for factors HOT 5
- xreg with predicted values
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