**NEW:** Refactored `clustering.py`; we now support three clustering methods: `MovM`, `CircHAC`, and `CircKMeans`.
See the [docs](https://circstat.github.io/pycircstat2/reference/clustering/) and the [example notebook](https://github.com/circstat/pycircstat2/blob/main/examples/T5-clustering.ipynb) for usage.
What's Changed * add: `equal_median_test()` * add: `angular_randomisation_test()` by elhananby in https://github.com/circstat/pycircstat2/pull/10 * change: `circ_dist` and `circ_pairdist` now support various kinds of distance measurement. * change: renamed `equal_median_test` to `common_median_test`, `circ_anova_test` to `circ_anova`, `aacorr` and `alcorr` to `circ_corrcc` and `circ_corrcl`
New Contributors * elhananby made their first contribution in https://github.com/circstat/pycircstat2/pull/10
Revamped `pycircstat2.regression` module, along with various bug fixes.
The `CLRegression(model_type="mean")` and `CCRegression` classes have been ported directly from the `lm.circular.cl` and `lm.circular.cc` functions of the R **circular** package. Furthermore, `CLRegression` introduces support for fitting the concentration parameter using `CLRegression(model_type="kappa")` and implementing the mixed model from Section 6.4 of Fisher (1993) with `CLRegression(model_type="mixed")`.
See this [tutorial notebook](https://github.com/circstat/pycircstat2/blob/main/examples/T4-regression.ipynb) for more examples.