Add UnobservedComponents statsmodels wrapper

[juanitorduz]

Reference Issues/PRs

Fixes #1371

What does this implement/fix? Explain your changes.

This PR wraps the UnobservedComponents from statsmodels. We follow closely the existing implementation sktime/forecasting/ets.py using the _StatsModelsAdapter class (a minor change was added in order to support exog variables).

Does your contribution introduce a new dependency? If yes, which one?

No

What should a reviewer concentrate their feedback on?

In this initial PR I provide a basic implementation of the wrapper. Still, I wanna make sure I understand what are the requirements the code needs in order to merge to main. Concretely here are my questions:

Main Questions:

• The docstrings of the original statsmodels class UnobservedComponents is very complete and gives a clear description of the model and the level variable which determines the structure of the state space model. How much should I add to the doctrings on the sktime implementation?

• Which kind of test should I write? Probably a couple of test ensuring the statsmodels implementation agrees with this one.

• Should I add this model to the examples/01_forecasting.ipynb notebook? Any other place where I should add more examples on this new estimator?

• Any other feedback or suggestion?

Minor Questions

• I wanted to add some useful plotting functions to this wrapper. Unfortunately the simple method plot_components fils because a TypeError: float() argument must be a string or a number, not 'Period'. Have you encounter this type of error in the past? It seems the internal plotting functions do not handle Period types.

For all contributions

• I've added myself to the list of contributors.
• I've added unit tests and made sure they pass locally.

For new estimators

• I've added complete doc-strings.
• I've added the estimator to the online documentation.
• I've updated the existing example notebooks or provided a new one to showcase how my estimator works.

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[juanitorduz]

In c6180a7 I added the first test to compare with the original implementation from statsmodels (plus an additional docs fix 4129b77)

[juanitorduz]

In 68f920d I added the UnobservedComponets estimator into the 01_forecasting notebook (section 2.5)

[juanitorduz]

In 884828a I added the model into the online documentation.

I think this draft PR is ready for a first review from the maintainers :)

[juanitorduz]

In 95ccf6e I added the doc-strings. Mostly taken from the ones in statsmodels. Again, I am not sure how much information should be added. Feedback is welcome :)

[mloning]

Hi @juanitorduz, I had a quick look and I think this looks very good! Only two minor comments. I haven't looked at the notebook changes yet.

[juanitorduz]

@mloning I do not understand why the Azure pipelines are failing in 19093fc 😢 ... any tip?

Update: I waited a day and push an empty commit (8009d52) to trigger the ci/cd and the azure pipelines are not failing 😄 !

[mloning]

All looks good to me now! The links now also reader correctly and directly link to the statsmodels online docs! Thanks @juanitorduz

The Azure pipeline failures were due to #1415 but all resolved now.

I'll merge in the next couple of days if nobody else comments.

[fkiraly]

Great addition!

However, there are - probably accidentally - massive changes to the forecasting notebook!
These should be reverted before we merge.

[juanitorduz]

Great addition!

However, there are - probably accidentally - massive changes to the forecasting notebook!
These should be reverted before we merge.

Ups! by looking into https://app.reviewnb.com/alan-turing-institute/sktime/pull/1394/files/ I see that in the master branch the notebook does not have any cell outputs 🙈 . I will fix this.

[juanitorduz]

Great addition!
However, there are - probably accidentally - massive changes to the forecasting notebook!
These should be reverted before we merge.

Ups! by looking into https://app.reviewnb.com/alan-turing-institute/sktime/pull/1394/files/ I see that in the master branch the notebook does not have any cell outputs 🙈 . I will fix this.

By looking into the diff and https://app.reviewnb.com/alan-turing-institute/sktime/pull/1394/files/ it seems juanitorduz@f2f939c and juanitorduz@9ff3d3f solved the problem.

Remark (specially for future self XD): I had to clear the notebook output twice: (1) The first one in VSCode (my IDE) which actually changed a bit the notebook structure (json order?) and then (2) restart using Jupyter notebooks (Anaconda), which solved the "high" number of changes issue 😃 !

[fkiraly]

Yes, thanks for fixing the notebook.

Unrelated, we may later want to add the automated estimator list to section 2, using all_estimators - though that's better a separate PR.