Maximum Likelihood for Interval Censored Data: Consistency and Computation
将标准凸优化技术应用于区间删失数据分析，给出了Turnbull自一致估计为最大似然估计的可验证条件，并提供了最大似然估计几乎必然收敛到真实分布函数的充分条件。
Standard convex optimization techniques are applied to the analysis of interval censored data. These methods provide easily verifiable conditions for the self-consistent estimator proposed by Turnbull (1976) to be a maximum likelihood estimator and for checking whether the maximum likelihood estimate is unique. A sufficient condition is given for the almost sure convergence of the maximum likelihood estimator to the true underlying distribution function.