Maximum Likelihood Estimation of a Distribution Function with Monotone Failure Rate Based on Censored Observations

摘要

The maximum likelihood estimator of a distribution function with monotone 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. (Author)