Maximum Likelihood Estimation for Two-Parameter Decreasing Hazard Rate Distributions Using Censored Data
研究了混合指数或“加工硬化”型递减风险率分布的形状和尺度参数的最大似然估计问题，给出了混合分布的充分条件以确保风险率正则性，并提供了计算方法及应用。
Problems of maximum likelihood estimation are discussed for shape and scale parameters from certain decreasing hazard rate distributions, typically either mixed-exponential or "work-hardened." Sufficient conditions on the mixing distribution are given that guarantee regular behavior of the hazard rate and that ensure, even with highly censored data, that the MLE's exist from such DHR distributions whenever the sample satisfies a certain condition; otherwise a constant hazard rate is estimated as a limiting case. Some computational methods are given and applications made.