Semi-parametric estimation of incubation and generation times by means of Laguerre polynomials

Kreiss, Alexander and Van Keilegom, Ingrid (2022) Semi-parametric estimation of incubation and generation times by means of Laguerre polynomials. Journal of Nonparametric Statistics, 34 (3). 570 - 606. ISSN 1048-5252

Text (Kreiss_semi-parametric-estimation-of-incubation--published) - Published Version Available under License Creative Commons Attribution. Download (3MB)

• Author
• Scopus publication

Abstract

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 transmission 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.

Item Type:	Article
Official URL:	https://www.tandfonline.com/journals/gnst20
Additional Information:	© 2022 The Authors
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	10 Jan 2022 12:06
Last Modified:	16 Nov 2024 07:21
URI:	http://eprints.lse.ac.uk/id/eprint/113376

Actions (login required)

View Item