[MNT] [Dependabot](deps): Update statsmodels requirement from <0.15.0,>=0.12.1 to >=0.12.1,<0.16.0

[dependabot]

Updates the requirements on statsmodels to permit the latest version.

Release notes

Sourced from statsmodels's releases.

Release 0.15.0

The statsmodels developers are happy to announce the release of 0.15.0. 358 issues were closed in this release and 655 pull requests were merged. Major new features include:

• Standardized on rng for controlling randomness across the package (SPEC 007), replacing seed/random_state
• Functions with variable-length tuple returns now return documented NamedTuple results instead
• A new abstracted formula engine that supports both patsy and formulaic as the backend
• Support for Polars DataFrames and Series as model input
• Switched the build backend from setuptools to meson-python
• New robust estimators: CovDetMCD, CovDetS, CovDetMM, and RLMDetSMM
• New tests: Diebold-Mariano, Pesaran-Timmermann, Jonckheere-Terpstra, Leybourne-McCabe, and a delete-k block jackknife estimator
• The Hamilton filter, local false discovery rate correction, and an L1-penalized GLM solver
• HurdleCountModel gained fit_regularized, and MICEData is now iterable

This release also raises the minimum supported versions of NumPy, SciPy, and pandas, and tightens input validation for many string-valued options across the package (invalid values that previously failed silently or with a confusing error now raise a clear ValueError). A handful of long-standing bugs in seldom-exercised code paths were also corrected as part of a systematic coverage audit this cycle, some of which change numerical output for affected models. See the release notes for the complete list of enhancements, breaking changes, and bug fixes.

Commits

• 278ff99 Merge pull request #10211 from bashtage/update-release-note
• ab3f3bc DOC: Final release note
• 9307ef1 Merge pull request #8712 from bdpedigo/nobs-style
• 463e5c5 Merge pull request #10210 from Panzerkampfwagen-del/mice-data-iterable
• cc734d8 Merge branch 'main' into mice-data-iterable
• 2912b84 Merge pull request #10209 from Panzerkampfwagen-del/var-df-model-docstring
• 279b9f4 ENH: make MICEData iterable, yielding successive imputed datasets
• ce7f2c0 DOC: clarify VARResults.df_model counts parameters per equation
• d1e1875 Merge pull request #10205 from bashtage/fix-hurdle-and-l1-cov
• bb385fb Merge pull request #10208 from bashtage/update-release-note
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[amotl]

According to CI, this patch currently fails due to two types of errors:

TypeError: ETSResults.simulate() got an unexpected keyword argument 'random_state'
TypeError: ccf() got an unexpected keyword argument 'unbiased'

[amotl]

TypeError: ETSResults.simulate() got an unexpected keyword argument 'random_state'

@siddharth7113 already reported that one. Thanks!

• [BUG] _StatsModelsAdapter passes random_state to statsmodels get_prediction, breaking predict_interval on statsmodels 0.15 sktime#10968

@aryamanDutta swiftly submitted a patch to sktime. Thanks!

• [BUG] Fix random_state handling in statsmodels adapter sktime#10972

We are exercising the outcome with a probing patch separately from this one.

• [MNT] Probe statsmodels 0.15 with sktime-next #137

[amotl]

This will converge positively after sktime has been improved.

• [BUG] Fix random_state handling in statsmodels adapter sktime#10972

[dependabot]

Dependabot tried to update this pull request, but something went wrong. We're looking into it, but in the meantime you can retry the update by commenting @dependabot recreate.