A law of the iterated logarithm for error density estimator in censored linear regression. Issue 2 (3rd April 2022) - Cheng, Fuxia
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.