Doubly censored data in the Kaplan-Meier estimator documentation

[lisandrojim]

Hello,

I am fitting a Kaplan-Meier estimator with doubly censored data. But I get an error. To reproduce the error use the example below.

from relife.nonparametric import KaplanMeier as KM
km = KM()
km.fit(time=np.array([1,2,3]),event=np.array([1,0,2]))

The error is:

  File ~/relife/nonparametric.py:54 in _estimate
    raise ValueError("event values must be in [0,1]")
ValueError: event values must be in [0,1]

But the documentation says that event 2 is used to flag an event as left-censored.

[tomguillon]

Thank you for your comments.
The Kaplan-Meier estimator cannot handle left censoring and right censoring. This is an error in the documentation that needs to be corrected. If you are interested in a non-parametric algorithm that takes into account all possible censorships, this is the Turnbull algorithm. It is planned to implement it in a future version.

[21ch216]

Turnbull estimator is added for a future release (refactoring branch merged very soon). I'll make sure that the documentation is more explicit and add more control on the data one user can pass to the fit method depending on the type of object.