statsforecast
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Nixtla
Lightning ⚡️ fast forecasting with statistical and econometric models.
- feat: new version GA sklearn syntax - feat: add functional fit/predict - feat: new tests - feat: add fit/predict classes - feat: add repr - feat: add core version...
I am trying to solve a timeseries problem with intermittent zero demand in the timeframe(Monthly data). I am getting this warning/error. /opt/conda/lib/python3.7/site-packages/statsforecast/arima.py:866: RuntimeWarning: divide by zero encountered in log return...
**Describe the bug** If I run the _ets model_ as described in the [references](https://nixtla.github.io/statsforecast/Getting_Started_with_Auto_Arima_and_ETS) (exact same code, same data), I get the error below. Main gist is from these lines:...
**Describe the bug** Related to #84 We implemented the `statsforecast` integration in pycaret using the sktime adapter. On implementing cross-validation, we noticed that the first model training is slow (for...
See #175, and https://github.com/Nixtla/hierarchicalforecast/issues/34
**Describe the bug** Under certain conditions the _warnings_ module is called in line 935 in statsforecast/ets.py but it is never imported -> an error is thrown if the line is...
Hello, I saw that when running Naive7/Naive1 the function accepted external regressors (xreg) as an argument, but they do not do anything with the input.
Given it is known that first run takes alot of time: why there is no option to do something like https://stackoverflow.com/questions/21370102/can-i-compile-numba-in-the-setup-phase-of-a-unit-test ? or anything better?
