UserWarning: NotImplementedWarning: NaiveForecaster does not have a custom `update` method implemented. NaiveForecaster will be refit each time `update` is called.

In version 0.5.3, there was no problem calling the ‘update’ method using the NaiveForecaster. However, since version 0.6.0, I receive the following warning:

UserWarning: NotImplementedWarning: NaiveForecaster does not have a custom updatemethod implemented. NaiveForecaster will be refit each timeupdate is called.

The update method is important to bootstrap prediction intervals. When will this be available again?

Expected behavior The expected behavior is that the model is not refit when ‘update’ is called.

Additional context

Versions System: python: 3.8.8 (default, Apr 13 2021, 12:59:45) [Clang 10.0.0 ] executable: /Users/muhlbach/opt/anaconda3/envs/stable/bin/python machine: macOS-10.16-x86_64-i386-64bit

Python dependencies: pip: 21.0.1 setuptools: 52.0.0.post20210125 sklearn: 0.24.1 sktime: 0.6.0 statsmodels: 0.12.2 numpy: 1.18.5 scipy: 1.6.2 Cython: 0.29.23 pandas: 1.1.3 matplotlib: 3.3.4 joblib: 1.0.1 numba: 0.50.1 pmdarima: 1.8.0 tsfresh: None

[muhlbach]

@mloning, sorry I didn’t get back to you in time. Setting update_params=False worked as a charm! For future reference, where can I find the changes you implement from version to version? I haven’t been able to locate them online.

[mloning]

Sure, feel free to add the link and open the issue! We could also have something like a table of contents at the top.