Important: we dropped Patsy as our formula framework, and adopted Formulaic. Will the latter is less mature than Patsy, we feel the core capabilities are satisfactory and it provides new opportunities.
New features - Parametric models with formulas are able to be serialized now. - a `_scipy_callback` function is available to use in fitting algorithms.
0.25.7
API Changes - Adding `cumulative_hazard_at_times` to NelsonAalenFitter
Bug fixes - Fixed error in `CoxPHFitter` when entry time == event time. - Fixed formulas in AFT interval censoring regression. - Fixed `concordance_index_` when no events observed - Fixed label being overwritten in ParametricUnivariate models
0.25.6
New features - Parametric Cox models can now handle left and interval censoring datasets.
Bug fixes - "improved" the output of `add_at_risk_counts` by removing a call to `plt.tight_layout()` - this works better when you are calling `add_at_risk_counts` on multiple axes, but it is recommended you call `plt.tight_layout()` at the very end of your script. - Fix bug in `KaplanMeierFitter`'s interval censoring where max(lower bound) < min(upper bound).
0.25.5
API Changes - `check_assumptions` now returns a list of list of axes that can be manipulated
Bug fixes - fixed error when using `plot_partial_effects` with categorical data in AFT models - improved warning when Hessian matrix contains NaNs. - fixed performance regression in interval censoring fitting in parametric models - `weights` wasn't being applied properly in NPMLE
0.25.4
New features - New baseline estimator for Cox models: ``piecewise`` - Performance improvements for parametric models `log_likelihood_ratio_test()` and `print_summary()` - Better step-size defaults for Cox model -> more robust convergence.
Bug fixes - fix `check_assumptions` when using formulas.
0.25.3
New features - `survival_difference_at_fixed_point_in_time_test` now accepts fitters instead of raw data, meaning that you can use this function on left, right or interval censored data.
API Changes - See note on `survival_difference_at_fixed_point_in_time_test` above.
Bug fixes - fix `StatisticalResult` printing in notebooks - fix Python error when calling `plot_covariate_groups` - fix dtype mismatches in `plot_partial_effects_on_outcome`.