lifelines

• adding plot_loglogs to KaplanMeierFitter
• added a (correct) check to see if some columns in a dataset will cause convergence problems.
• removing flat argument in plot methods. It was causing confusion. To replicate it, one can set ci_force_lines=True and show_censors=True.
• adding strata keyword argument to CoxPHFitter on initialization (ex: CoxPHFitter(strata=['v1', 'v2']). Why? Fitters initialized with strata can now be passed into k_fold_cross_validation, plus it makes unit testing strata fitters easier.
• If using strata in CoxPHFitter, access to strata specific baseline hazards and survival functions are available (previously it was a blended valie). Prediction also uses the specific baseline hazards/survivals.
• performance improvements in CoxPHFitter - should see at least a 10% speed improvement in fit.

• deprecates Pandas versions before 0.18.
• throw an error if no admissable pairs in the c-index calculation. Previously a NaN was returned.

• 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.

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

• Ability to specify default printing in statistical tests with the suppress_print keyword argument (default False).
• For the multivariate log rank test, the inverse step has been replaced with the generalized inverse. This seems to be what other packages use.
• Adding more robust cross validation scheme based on issue #67.
• fixing regression_dataset in datasets.