School of Mathematics and Information Science, Jiangxi Normal University; School of Finance and Statistics, East China Normal University

The accelerated failure time model provides a natural formulation
of the effects of covariates on the failure time variable. The presence of censoring poses
major challenges in the semi-parametric analysis. The existing semi-parametric estimators
are computationally intractable. In this article we propose an unbiased transformation for
the potential censored response variable, thus least square estimators of regression
parameters can be gotten easily. The resulting estimators are consistent and asymptotically
normal. Based on these, we can get a strongly consistent K-M estimator for the distribution
of random error. Extensive simulation studies show that the asymptotic approximations are
accurate in practical situations.