0.21.2 - 2019-05-16 New features New regression model: PiecewiseExponentialRegressionFitter is available. See blog post here: https://dataorigami.net/blogs/napkin-folding/churn Regression models have a new method log_likelihood_ratio_test that computes, you guessed it, the log-likelihood ratio test. Previously this was an internal API that is being exposed. API changes The default behavior of the predict method on non-parametric estimators (KaplanMeierFitter, etc.) has changed from (previous) linear interpolation to (new) return last value. Linear interpolation is still possible with the interpolate flag. removing _compute_likelihood_ratio_test on regression models. Use log_likelihood_ratio_test now
0.19.3 New features new AFT models: LogNormalAFTFitter and LogLogisticAFTFitter. AFT models now acc...
0.23.6 - 2020-01-07 New features New univariate model, SplineFitter, that uses cubic splines to mod...
0.22.6 New features conditional_after works for CoxPHFitter prediction models Bug fixes API Chang...
0.25.4 - 2020-08-26 New features New baseline estimator for Cox models: piecewise Performance impro...
0.19.0 New features New regression model WeibullAFTFitter for fitting accelerated failure time mode...
0.18.0 LogNormalFitter is a new univariate fitter you can use. WeibullFitter now correctly returns ...
0.19.2 New features ParametricUnivariateFitters, like WeibullFitter, have smoothed plots when plott...
0.13.0 removes is_significant and test_result from StatisticalResult. Users can instead choose thei...
0.26.0 - 2021-05-26 New features .BIC_ is now present on fitted models. CoxPHFitter with spline bas...
0.24.0 - 2020-02-20 This version and future versions of lifelines no longer support py35. Pandas 1....
New features Ability to create custom parametric regression models by specifying the cumulative haz...
0.22.1 New features New univariate model, GeneralizedGammaFitter. This model contains many sub-mode...
0.25.0 - 2020-07-27 New features Formulas! lifelines now supports R-like formulas in regression mod...
0.18.1 bug fixes in LogNormalFitter variance estimates improve convergence of LogNormalFitter. We n...
0.22.4 - 2019-09-04 New features Some performance improvements to regression models. lifelines will...
0.19.3 New features new AFT models: LogNormalAFTFitter and LogLogisticAFTFitter. AFT models now acc...
0.23.6 - 2020-01-07 New features New univariate model, SplineFitter, that uses cubic splines to mod...
0.22.6 New features conditional_after works for CoxPHFitter prediction models Bug fixes API Chang...
0.25.4 - 2020-08-26 New features New baseline estimator for Cox models: piecewise Performance impro...
0.19.0 New features New regression model WeibullAFTFitter for fitting accelerated failure time mode...
0.18.0 LogNormalFitter is a new univariate fitter you can use. WeibullFitter now correctly returns ...
0.19.2 New features ParametricUnivariateFitters, like WeibullFitter, have smoothed plots when plott...
0.13.0 removes is_significant and test_result from StatisticalResult. Users can instead choose thei...
0.26.0 - 2021-05-26 New features .BIC_ is now present on fitted models. CoxPHFitter with spline bas...
0.24.0 - 2020-02-20 This version and future versions of lifelines no longer support py35. Pandas 1....
New features Ability to create custom parametric regression models by specifying the cumulative haz...
0.22.1 New features New univariate model, GeneralizedGammaFitter. This model contains many sub-mode...
0.25.0 - 2020-07-27 New features Formulas! lifelines now supports R-like formulas in regression mod...
0.18.1 bug fixes in LogNormalFitter variance estimates improve convergence of LogNormalFitter. We n...
0.22.4 - 2019-09-04 New features Some performance improvements to regression models. lifelines will...
0.19.3 New features new AFT models: LogNormalAFTFitter and LogLogisticAFTFitter. AFT models now acc...
0.23.6 - 2020-01-07 New features New univariate model, SplineFitter, that uses cubic splines to mod...
0.22.6 New features conditional_after works for CoxPHFitter prediction models Bug fixes API Chang...