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

• Record Type: Journal Article
• Authors: Cheng, Fuxia
• Is Part Of: Journal of nonparametric statistics. Volume 34:Issue 2(2022)
• Page Start: 283
• Page End: 298
• Publication Date: 2022-04-03
• Subjects: Kaplan-Meier estimator -- right censored data -- bandwidth -- kernel density estimation -- LIL; Primary: 62N01 -- Secondary: 62N02; Nonparametric statistics -- Periodicals; 519.5
• DOI: 10.1080/10485252.2022.2042814
• Languages: English
• ISSNs: 1048-5252

Abstract

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.