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 https://github.com/pietg/incubationtime.

翻译：我们分析了单间隔和双间隔删失模型下潜伏期分布函数的非参数估计方法。传统方法通常采用威布尔分布、对数正态分布或伽马分布等参数族进行估计。本文提出的非参数估计方法相较于传统参数方法能更贴近数据特征。我们还给出了离散模型显式极限分布，并将其应用于置信区间的计算。该研究成果为连续模型分析提供了补充。文中涉及的R语言计算脚本已发布于https://github.com/pietg/incubationtime。