Miscellanea. On the linear transformation model for censored data
针对删失数据下线性变换模型估计量在删失变量支撑较短时存在渐近偏误的问题，提出一种简单修正方法，并通过数值模拟验证新方法在有限样本下的表现优于原方法。
Recently Cheng, Wei & Ying (1995, 1997) proposed a class of estimation procedures for semiparametric linear transformation models with censored observations. When the support of the censoring variable is shorter than that of the failure time, the estimators are asymptotically biased. In this paper, we present a simple modification of Cheng's estimation procedures for the regression parameters. Through extensive numerical studies with practical sample sizes, we find that the new proposals perform well, but the original interval estimators may not have correct coverage probabilities when censoring is heavy. Prediction procedures for the survival probabilities of future subjects are also modified accordingly.