sksurv.nonparametric.CensoringDistributionEstimator

class sksurv.nonparametric.CensoringDistributionEstimator

Kaplan–Meier estimator for the censoring distribution.

__init__()

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__()	Initialize self.
fit(y)	Estimate censoring distribution from training data.
predict_ipcw(y)	Return inverse probability of censoring weights at given time points.
predict_proba(time)	Return probability of an event after given time point.

fit(y)

Estimate censoring distribution from training data.

Parameters:y (structured array, shape = (n_samples,)) – A structured array containing the binary event indicator as first field, and time of event or time of censoring as second field. Returns: Return type:self

predict_ipcw(y)

Return inverse probability of censoring weights at given time points.

\(\omega_i = \delta_i / \hat{G}(y_i)\)

Parameters:y (structured array, shape = (n_samples,)) – A structured array containing the binary event indicator as first field, and time of event or time of censoring as second field. Returns:ipcw – Inverse probability of censoring weights. Return type:array, shape = (n_samples,)

predict_proba(time)

Return probability of an event after given time point.

\(\hat{S}(t) = P(T > t)\)

Parameters:time (array, shape = (n_samples,)) – Time to estimate probability at. Returns:prob – Probability of an event. Return type:array, shape = (n_samples,)