sksurv.nonparametric.kaplan_meier_estimator(event, time_exit, time_enter=None, time_min=None)

Kaplan-Meier estimator of survival function.

See [1] for further description.

  • event (array-like, shape = (n_samples,)) – Contains binary event indicators.
  • time_exit (array-like, shape = (n_samples,)) – Contains event/censoring times.
  • time_enter (array-like, shape = (n_samples,), optional) – Contains time when each individual entered the study for left truncated survival data.
  • time_min (float, optional) – Compute estimator conditional on survival at least up to the specified time.

  • time (array, shape = (n_times,)) – Unique times.
  • prob_survival (array, shape = (n_times,)) – Survival probability at each unique time point. If time_enter is provided, estimates are conditional probabilities.


Creating a Kaplan-Meier curve:

>>> x, y = kaplan_meier_estimator(event, time)
>>> plt.step(x, y, where="post")
>>> plt.ylim(0, 1)


[1]Kaplan, E. L. and Meier, P., “Nonparametric estimation from incomplete observations”, Journal of The American Statistical Association, vol. 53, pp. 457-481, 1958.