v0.18.0
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1035 commits
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since this release
0.18.0
LogNormalFitteris a new univariate fitter you can use.WeibullFitternow correctly returns the confidence intervals (previously returned only NaNs)WeibullFitter.print_summary()displays p-values associated with its parameters not equal to 1.0 - previously this was (implicitly) comparing against 0, which is trivially always true (the parameters must be greater than 0)ExponentialFitter.print_summary()displays p-values associated with its parameters not equal to 1.0 - previously this was (implicitly) comparing against 0, which is trivially always true (the parameters must be greater than 0)ExponentialFitter.plotnow displays the cumulative hazard, instead of the survival function. This is to make it easier to compare toWeibullFitterandLogNormalFitter- Univariate fitters'
cumulative_hazard_at_times,hazard_at_times,survival_function_at_timesreturn pandas Series now (use to be numpy arrays) - remove
alphakeyword from all statistical functions. This was never being used. - Gone are astericks and dots in
print_summaryfunctions that represent signficance thresholds. - In models'
summary(includingprint_summary), thelog(p)term has changed to-log2(p). This is known as the s-value. See https://lesslikely.com/statistics/s-values/ - introduce new statistical tests between univariate datasets:
survival_difference_at_fixed_point_in_time_test,... - new warning message when Cox models detects possible non-unique solutions to maximum likelihood.
- Generally: clean up lifelines exception handling. Ex: catch
LinAlgError: Matrix is singular.and report back to the user advice.