We analyze nonparametric estimators for the distribution function of the incubation time in the singly and doubly interval censoring model. The classical approach is to use parametric families like Weibull, log-normal or gamma distributions in the estimation procedure. We propose nonparametric estimates which stay closer to the data than the classical parametric methods. We also give explicit limit distributions for discrete versions of the models and apply this to compute confidence intervals. The methods complement the analysis of the continuous model. R scripts for computation of the estimates are provided on GitHub.

翻译：我们分析了单间隔和双间隔删失模型中潜伏期分布函数的非参数估计方法。经典方法是在估计过程中使用参数族，如威布尔分布、对数正态分布或伽马分布。本文提出的非参数估计比经典参数方法更贴近数据。我们还给出了离散模型版本的显式极限分布，并将其应用于置信区间的计算。这些方法补充了对连续模型的分析。用于计算估计值的R脚本已在GitHub上提供。