Doubleml

- Update citation info to publication in Journal of Statistical Software, rename helper function and fix links and GH actions 191

- Increment package requirements and update workflows for Python 3.9 (add tests for Python 3.12) [247](https://github.com/DoubleML/doubleml-for-py/pull/247) [#175](https://github.com/DoubleML/doubleml-docs/pull/175)

- Additional example for ranking treatment effects (by [Apoorva Lal](https://github.com/apoorvalal)) [#173](https://github.com/DoubleML/doubleml-docs/pull/173) [#174](https://github.com/DoubleML/doubleml-docs/pull/174)

- Maintenance documentation [172](https://github.com/DoubleML/doubleml-docs/pull/172)

- **Release highlight:** Sample-selections models as `DoubleMLSMM` class (by [Michaela Kecskésová](https://github.com/mychaelka)) [#231](https://github.com/DoubleML/doubleml-for-py/pull/231) [#235](https://github.com/DoubleML/doubleml-for-py/pull/235) [#171](https://github.com/DoubleML/doubleml-docs/pull/171)
- **API change:** Remove options `apply_crossfitting` and `dml_procedure` from the `DoubleML` class [227](https://github.com/DoubleML/doubleml-for-py/pull/227) [#166](https://github.com/DoubleML/doubleml-docs/pull/166)
- Restructure the package to improve readability and maintainability [225](https://github.com/DoubleML/doubleml-for-py/pull/225)
- Add a `DoubleMLFramework` class to combine multiple DoubleML models (aggregation of estimates, bootstrap, and CI-procedures [226](https://github.com/DoubleML/doubleml-for-py/pull/226) [#169](https://github.com/DoubleML/doubleml-docs/pull/169)
- Enable the use of external predictions for short models in benchmarks (by [Lucien](https://github.com/lucien1011)) [#238](https://github.com/DoubleML/doubleml-for-py/pull/238) [#239](https://github.com/DoubleML/doubleml-for-py/pull/239)
- Add the `gain_statistics` to `utils` for sensitivity analysis [229](https://github.com/DoubleML/doubleml-for-py/pull/229)

- Maintenance documentation [162](https://github.com/DoubleML/doubleml-docs/pull/162) [#163](https://github.com/DoubleML/doubleml-docs/pull/163) [#164](https://github.com/DoubleML/doubleml-docs/pull/164) [#165](https://github.com/DoubleML/doubleml-docs/pull/165) [#167](https://github.com/DoubleML/doubleml-docs/pull/167) [#168](https://github.com/DoubleML/doubleml-docs/pull/168)

- Maintenance package [225](https://github.com/DoubleML/doubleml-for-py/pull/225) [#229](https://github.com/DoubleML/doubleml-for-py/pull/229) [#246](https://github.com/DoubleML/doubleml-for-py/pull/246)

- **Release highlight:** Add weights to `DoubleMLIRM` class to extend sensitivity to GATEs etc. [220](https://github.com/DoubleML/doubleml-for-py/pull/220) [#229](https://github.com/DoubleML/doubleml-for-py/pull/229) [#155](https://github.com/DoubleML/doubleml-docs/pull/155) [#161](https://github.com/DoubleML/doubleml-docs/pull/161)

- Extend GATE and CATE estimation to the `DoubleMLPLR` class [220](https://github.com/DoubleML/doubleml-for-py/pull/220) [#155](https://github.com/DoubleML/doubleml-docs/pull/155)

- Enable the use of external predictions for `DoubleML` classes [221](https://github.com/DoubleML/doubleml-for-py/pull/221) [#159](https://github.com/DoubleML/doubleml-docs/pull/159)

- Implementing utility classes and functions (gain statistics and dummy learners) [221](https://github.com/DoubleML/doubleml-for-py/pull/221) [#222](https://github.com/DoubleML/doubleml-for-py/pull/222) [#229](https://github.com/DoubleML/doubleml-for-py/pull/229) [#161](https://github.com/DoubleML/doubleml-docs/pull/161)

- Extend example Gallery [153](https://github.com/DoubleML/doubleml-docs/pull/153) [#158](https://github.com/DoubleML/doubleml-docs/pull/158) [#161](https://github.com/DoubleML/doubleml-docs/pull/161)

- Maintenance documentation [157](https://github.com/DoubleML/doubleml-docs/pull/157) [#160](https://github.com/DoubleML/doubleml-docs/pull/160)

- Maintenance package [223](https://github.com/DoubleML/doubleml-for-py/pull/223) [#224](https://github.com/DoubleML/doubleml-for-py/pull/224)

- **Release highlight:** Benchmarking for Sensitivity Analysis (omitted variable bias) [211](https://github.com/DoubleML/doubleml-for-py/pull/211)

- Policy tree estimation for the `DoubleMLIRM` class [212](https://github.com/DoubleML/doubleml-for-py/pull/212)

- Extending sensitivity and policy tree documentation in User Guide and Example Gallery [148](https://github.com/DoubleML/doubleml-docs/pull/148) [#150](https://github.com/DoubleML/doubleml-docs/pull/150)

- The package requirements are set to Python 3.8 or higher [211](https://github.com/DoubleML/doubleml-for-py/pull/211)

- Maintenance documentation [149](https://github.com/DoubleML/doubleml-docs/pull/149)

- Maintenance package [213](https://github.com/DoubleML/doubleml-for-py/pull/213)

- Fix install requirements for 0.6.2 [208](https://github.com/DoubleML/doubleml-for-py/pull/208)