Abstract
We consider the strong consistency of the nonparametric estimation of error density in linear regression with right censored data. The estimator is defined to be the kernel-smoothed estimator of error density, which makes use of the Kaplan-Meier estimator of the error distribution. We establish a point-wise law of the iterated logarithm for kernel-type error density estimator in censored Linear Regression.
2010 AMS subject classifications:
Acknowledgements
The author thank a past Editor-in-Chief, an Associate Editor and a reviewer for their valuable comments, which have improved the former version of the paper.
Disclosure statement
No potential conflict of interest was reported by the author(s).