This work implements two function kaplan_meier_estimator and kaplan_meier_estimator_w
The former one speed up the scikit survival kaplan meier curve using numba, the latter one is a weighted version of the former one.
to be used for Nearest Neighbors Weighted or Kenel Survival Estimator.
A blog
pip install git+https://github.com/yuvrajiro/fastkmefrom fastkme import kaplan_meier_estimator, kaplan_meier_estimator_w
import numpy as np
np.random.seed(0)
time = np.random.randint(0, 100, 100)
event = np.random.randint(0, 2, 100)
unique_time, survival_prob = kaplan_meier_estimator(time, event)This project is licensed under the MIT License - see the LICENSE.md file for details
## Acknowledgments
* This work is inspired by the scikit-survival package