v0.10
This release adds the ties argument to sksurv.linear_model.CoxPHSurvivalAnalysis to choose between Breslow’s and Efron’s likelihood in the presence of tied event times. Moreover, sksurv.compare.compare_survival() has been added, which implements the log-rank hypothesis test for comparing the survival function of 2 or more groups.
Enhancements
- Update API doc of predict function of boosting estimators (#75).
- Clarify documentation for GradientBoostingSurvivalAnalysis (#78).
- Implement Efron’s likelihood for handling tied event times.
- Implement log-rank test for comparing survival curves.
- Add support for scipy 1.3.1 (#66).
Bug fixes
- Re-add baseline_survival_ and cum_baseline_hazard_ attributes to sksurv.linear_model.CoxPHSurvivalAnalysis (#76).