[BUG] Modified VAR code to allow predict_quantiles of 0.5 (fixes #4742) #6441
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meraldoantonio
requested review from
achieveordie,
benHeid,
fkiraly and
yarnabrina
as code owners
fkiraly
reviewed
May 17, 2024
yarnabrina
requested changes
May 18, 2024
Comment on lines
+248
to
+250
| # A hacky way to coerce error-inducing alpha==1 into its approximant | ||
| if alpha >= 0.99999: | ||
| alpha = 0.99999 |
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Thoughts: can/should we document this hack for users, and if so, where?
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I think docstring modifications in these file do not get shown in read the docs. These are private methods (starting with _), and what all gets shown is only those of the base class.
Please let me know if this a misunderstanding.
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I mean, the class docstring, that gets overridden.
…tonio/sktime into var_0.5_quantile_error Merging
fkiraly
reviewed
May 19, 2024
| @@ -2649,7 +2649,8 @@ | |||
| "avatar_url": "https://avatars.githubusercontent.com/u/37468543?v=4", | |||
| "profile": "https://github.com/meraldoantonio", | |||
| "contributions": [ | |||
| "doc" | |||
| "doc", | |||
| "bug" | |||
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"bug" is for diagnosing or reporting bugs, but not bugfixes. Bugfixes fall under the "code" badge, so you can add both.
|
Merging for release. Since not blocking, the updates to docstring can be made in separate PR. |
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Reference Issues/PRs
Fixes #4742
What does this implement/fix? Explain your changes.
Previously, VAR produced an error when predicting quantiles with an alpha of 0.5. This issue arose because alpha was converted to a coverage of 1.0 in
_base, which was then reconverted to an alpha ("internal alpha") of 1.0 inside VAR's_predict_interval. An internal alpha of 1.0 is outside the acceptable range (0.0 to 1.0 exclusive) for statsmodels VAR.This change hackily coerces an internal alpha of 1.0 to 0.99999 to avoid this error.
Does your contribution introduce a new dependency? If yes, which one?
No
What should a reviewer concentrate their feedback on?
The hacky nature of this change
Did you add any tests for the change?
No
PR checklist
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maintainerstag - do this if you want to become the owner or maintainer of an estimator you added.See here for further details on the algorithm maintainer role.