azul

[FEAT] Use Dask and Spark clusters

3

**Is your feature request related to a problem? Please describe.** Scale StatsForecast using Dask and Spark clusters. **Describe the solution you'd like** Include [fugue](https://github.com/fugue-project/fugue) as a backend just as we...

[FEAT] Complete `mstl` handling multiple seasonalities and forecast model

2

- feat: move mstl to statsforecast/mstl - feat: complete mstl function (multiple seasonalities)

**Is your feature request related to a problem? Please describe.** The `cross_validation` method has the argument `input_size`; `forecast` should also have it.

[FEAT] Add environment variables for `njit`'s `cache=True` and `nogil=True`

1

**Is your feature request related to a problem? Please describe.** To speed up numba functions, [`cache=True`](https://numba.pydata.org/numba-doc/latest/user/jit.html?highlight=cache#cache) can be used to avoid compilation times each time the function is invoked; and...

**Is your feature request related to a problem? Please describe.** The `cross_validation` method should include a `level` parameter to compute prediction intervals.

**Is your feature request related to a problem? Please describe.** The library already has the `AutoARIMA` class but it would be helpful to have the `ARIMA` class. **Describe the solution...

Add update feature

4

Thanks a lot! I look forward to them. Another valuable feature to add is .update(). Then we don't need to re-train the models with hourly observations until the models get...

### Discussed in https://github.com/Nixtla/statsforecast/discussions/71 Originally posted by **tuttoaposto** March 8, 2022 1. Is it possible to get the bestfit model from the ```auto_arima_f()``` step in ```auto_arima()```? It would be nice...