ANN: statsmodels 0.15.0

Announcements
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The statsmodels developers are pleased to announce the release of statsmodels 0.15.0. It comes 3 years after the first release of 0.14.0. In total, 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.

Test coverage has been substantially increased, and many edge-case bugs have also been fixed.

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