Maximum Likelihood Estimation of a Distribution Function with Increasing Failure Rate Based on Censored Observations
针对任意右删失数据，推导了递增失效率分布函数的最大似然估计量，该估计量在正实数轴上处处有定义，而Kaplan-Meier估计量可能没有；通过Weibull分布的蒙特卡洛研究展示了其小样本性质。
The maximum likelihood estimator of a distribution function with increasing failure rate is derived based on a set of observations subject to arbitrary right censorship. This estimator is defined everywhere on the positive real line while the Kaplan-Meier estimator may not be. The small sample properties of this estimator are indicated by results of a Monte Carlo study for the Weibull distribution.