Regression Analysis with Randomly Right-Censored Data
H. Koul, V. Susarla, J. Van Ryzin
The Annals of Statistics · 1981 · Volume 9 · Issue 6
Abstract
This paper proposes a new estimator of the parameter vector in a linear regression model when the observations are randomly censored on the right and when the error distribution is unknown. This estimator is explicitly defined and easily computable. The paper contains sufficient conditions under which this estimator is mean square consistent and asymptotically normal. A numerical example is given.
Keywords
62G05, 62J05, 62N05, 62P10, asymptotically normal, consistent, Kaplan-Meier, least squares
Enable JavaScript for citation tools and additional paper interactions.