A nonparametric estimation for infectious diseases with latent period

被引：1
|
作者：
Wang, Wensheng [1 ]
Zhou, Hui [1 ]
Zhu, Anwei [2 ]
机构：
[1] Hangzhou Dianzi Univ, Sch Econ, Hangzhou 310018, Peoples R China
[2] Hangzhou Normal Univ, Coll Sci, Hangzhou, Peoples R China
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2022年 / 51卷 / 19期
基金：
中国国家自然科学基金;
关键词：
Nonparametric estimation; infection curve; epidemic; full smoothing estimation;
D O I：
10.1080/03610926.2020.1865402
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Predicting the future contagion of infectious diseases depends on the ability to estimate the current number of cases of infection. In this paper, a full smoothing method is proposed to evaluate the number of daily new cases of infection during the epidemic period. Under mild regularity assumptions, we obtain the consistency and asymptotic normality of the resulting estimator. Both simulated examples and a real data example are used for illustration.
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页码：6701 / 6718
页数：18
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