v0.22.5

0.22.5 - 2019-09-20

New features

• Improvements to the repr of models that takes into accounts weights.
• Better support for predicting on Pandas Series

Bug fixes

• Fixed issue where fit_interval_censoring wouldn't accept lists.
• Fixed an issue with AalenJohansenFitter failing to plot confidence intervals.

API Changes

• _get_initial_value in parametric univariate models is renamed _create_initial_point

v0.22.4

0.22.4 - 2019-09-04

New features

• Some performance improvements to regression models.
• lifelines will avoid penalizing the intercept (aka bias) variables in regression models.
• new utils.restricted_mean_survival_time that approximates the RMST using numerical integration against survival functions.

API changes

• KaplanMeierFitter.survival_function_'s' index is no longer given the name "timeline".

Bug fixes

• Fixed issue where concordance_index would never exit if NaNs in dataset.

v0.22.3

0.22.3

New features

• model's now expose a log_likelihood_ property.
• new conditional_after argument on predict_* methods that make prediction on censored subjects easier.
• new lifelines.utils.safe_exp to make exp overflows easier to handle.
• smarter initial conditions for parametric regression models.
• New regression model: GeneralizedGammaRegressionFitter

API changes

• removed lifelines.utils.gamma - use autograd_gamma library instead.
• removed bottleneck as a dependency. It offered slight performance gains only in Cox models, and only a small fraction of the API was being used.

Bug fixes

• AFT log-likelihood ratio test was not using weights correctly.
• corrected (by bumping) scipy and autograd dependencies
• convergence is improved for most models, and many exp overflow warnings have been eliminated.
• Fixed an error in the predict_percentile of LogLogisticAFTFitter. New tests have been added around this.

v0.22.2

0.22.2

New features

• lifelines is now compatible with scipy>=1.3.0

Bug fixes

• fixed printing error when using robust=True in regression models
• GeneralizedGammaFitter is more stable, maybe.
• lifelines was allowing old version of numpy (1.6), but this caused errors when using the library. The correctly numpy has been pinned (to 1.14.0+)

v0.22.1

0.22.1

New features

• New univariate model, GeneralizedGammaFitter. This model contains many sub-models, so it is a good model to check fits.
• added a warning when a time-varying dataset had instantaneous deaths.
• added a initial_point option in univariate parametric fitters.
• initial_point kwarg is present in parametric univariate fitters .fit
• event_table is now an attribute on all univariate fitters (if right censoring)
• improvements to lifelines.utils.gamma

API changes

• In AFT models, the column names in confidence_intervals_ has changed to include the alpha value.
• In AFT models, some column names in .summary and .print_summary has changed to include the alpha value.
• In AFT models, some column names in .summary and .print_summary includes confidence intervals for the exponential of the value.

Bug fixes

• when using censors_show in plotting functions, the censor ticks are now reactive to the estimate being shown.
• fixed an overflow bug in KaplanMeierFitter confidence intervals
• improvements in data validation for CoxTimeVaryingFitter

v0.22.0

New features

• Ability to create custom parametric regression models by specifying the cumulative hazard. This enables new and extensions of AFT models.
• percentile(p) method added to univariate models that solves the equation p = S(t) for t
• for parametric univariate models, the conditional_time_to_event_ is now exact instead of an approximation.

API changes

• In Cox models, the attribute hazards_ has been renamed to params_. This aligns better with the other regression models, and is more clear (what is a hazard anyways?)
• In Cox models, a new hazard_ratios_ attribute is available which is the exponentiation of params_.
• In regression models, the column names in confidence_intervals_ has changed to include the alpha value.
• In regression models, some column names in .summary and .print_summary has changed to include the alpha value.
• In regression models, some column names in .summary and .print_summary includes confidence intervals for the exponential of the value.
• Significant changes to internal AFT code.
• A change to how fit_intercept works in AFT models. Previously one could set fit_intercept to False and not have to set ancillary_df - now one must specify a DataFrame.

Bug fixes

• for parametric univariate models, the conditional_time_to_event_ is now exact instead of an approximation.

v0.21.3

0.21.3 - 2019-06-04

New features

• include in lifelines is a scikit-learn adapter so lifeline's models can be used with scikit-learn's API. See documentation here.
• CoxPHFitter.plot now accepts a hazard_ratios (boolean) parameter that will plot the hazard ratios (and CIs) instead of the log-hazard ratios.
• CoxPHFitter.check_assumptions now accepts a columns parameter to specify only checking a subset of columns.

Bug fixes

• covariates_from_event_matrix handle nulls better

v0.21.2

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.

v0.21.1

0.21.1 - 2019-04-26

New features

• users can provided their own start and stop column names in add_covariate_to_timeline
• PiecewiseExponentialFitter now allows numpy arrays as breakpoints

API changes

• output of survival_table_from_events when collapsing rows to intervals now removes the "aggregate" column multi-index.

Bug fixes

• fixed bug in CoxTimeVaryingFitter when ax is provided, thanks @j-i-l!

v0.21.0

0.21.0

New features

• weights is now a optional kwarg for parametric univariate models.
• all univariate and multivariate parametric models now have ability to handle left, right and interval censored data (the former two being special cases of the latter). Users can use the fit_right_censoring (which is an alias for fit), fit_left_censoring and fit_interval_censoring.
• a new interval censored dataset is available under lifelines.datasets.load_diabetes

API changes

• left_censorship on all univariate fitters has been deprecated. Please use the new
  api model.fit_left_censoring(...).
• invert_y_axis in model.plot(... has been removed.
• entries property in multivariate parametric models has a new Series name: entry

Bug fixes

• lifelines was silently converting any NaNs in the event vector to True. An error is now thrown instead.
• Fixed an error that didn't let users use Numpy arrays in prediction for AFT models