Lifelines 0.4.4

• Lots of improvements to numerical stability (but something things still need work)
• Additions to summary in CoxPHFitter.
• Make all prediction methods output a DataFrame
• Fixes bug in 1-d input not returning in CoxPHFitter
• Lots of new tests.

0.4.3

• refactoring of qth_survival_times: it can now accept an iterable (or a scalar still) of probabilities in the q argument, and will return a DataFrame with these as columns. If len(q)==1 and a single survival function is given, will return a scalar, not a DataFrame. Also some good speed improvements.
• KaplanMeierFitter and NelsonAalenFitter now have a _label property that is passed in during the fit.
• KaplanMeierFitter/NelsonAalenFitter's inital alpha value is overwritten if a new alpha value is passed
  in during the fit.
• New method for KaplanMeierFitter: conditional_time_to. This returns a DataFrame of the estimate:
  med(S(t | T>s)) - s, human readable: the estimated time left of living, given an individual is aged s.
• Adds option include_likelihood to CoxPHFitter fit method to save the final log-likelihood value.

Lifelines 0.4.2

0.4.2

• Massive speed improvements to CoxPHFitter.
• Additional prediction method: predict_percentile is available on CoxPHFitter and AalenAdditiveFitter. Given a percentile, p, this function returns the value t such that S(t | x) = p. It is a generalization of predict_median.
• Additional kwargs in k_fold_cross_validation that will accept different prediction methods (default is predict_median).
• Bug fix in CoxPHFitter predict_expectation function.
• Correct spelling mistake in newton-rhapson algorithm.
• datasets now contains functions for generating the respective datasets, ex: generate_waltons_dataset.
• Bumping up the number of samples in statistical tests to prevent them from failing so often (this a stop-gap)
• pep8 everything

Version 0.4.1

• CoxFitter is now known as CoxPHFitter
• refactoring some tests that used redundant data from lifelines.datasets.
• Adding cross validation: in utils is a new k_fold_cross_validation for model selection in regression problems.
• Change CoxPHFitter's fit method's display_output to False.
• fixing bug in CoxPHFitter's _compute_baseline_hazard that errored when sending Series objects to
  survival_table_from_events.
• CoxPHFitter's fit now looks to columns with too low variance, and halts NR algorithm if a NaN is found.
• Adding a Changelog.
• more sanitizing for the statistical tests =)