论文标题
通过Laguerre多项式进行孵育和发电时间的半参数估计
Semi-Parametric Estimation of Incubation and Generation Times by Means of Laguerre Polynomials
论文作者
论文摘要
在流行病中，许多有趣的数量（例如繁殖数量）取决于孵化期（从感染到症状发作的时间）和/或生成时间（直到新人被另一个受感染者感染的时间）。因此，对这两个数量的分布的估计是独特的。但是，这是一个具有挑战性的问题，因为通常无法获得这两个变量的精确观察结果。取而代之的是，在大流行的开始时，可以观察到感染对人的症状发作时间以及第一人称感染的窗口（例如，由于前往风险区域的旅行）。在本文中，我们建议一种基于laguerre-Polynomials的简单半参数估计方法，用于估计这些分布。我们提供详细的理论，以保持一致性，并通过仿真研究说明了小数据集的有限样本性能。
In epidemics many interesting quantities, like the reproduction number, depend on the incubation period (time from infection to symptom onset) and/or the generation time (time until a new person is infected from another infected person). Therefore, estimation of the distribution of these two quantities is of distinct interest. However, this is a challenging problem since it is normally not possible to obtain precise observations of these two variables. Instead, in the beginning of a pandemic, it is possible to observe for infection pairs the time of symptom onset for both people as well as a window for infection of the first person (e.g. because of travel to a risk area). In this paper we suggest a simple semi-parametric sieve-estimation method based on Laguerre-Polynomials for estimation of these distributions. We provide detailed theory for consistency and illustrate the finite sample performance for small datasets via a simulation study.
