|
Activity Number:
|
373
- Analysis of Duration Data, with Applications to the COVID-19 Pandemic
|
|
Type:
|
Topic-Contributed
|
|
Date/Time:
|
Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
|
|
Sponsor:
|
IMS
|
|
Abstract #319190
|
|
|
Title:
|
Estimation in the singly and doubly interval censored model
|
|
Author(s):
|
Piet Groeneboom*
|
|
Companies:
|
Delft University
|
|
Keywords:
|
nonparametric MLE;
kernel estimates;
Weibull distribution;
incubation time;
COVID-19
|
|
Abstract:
|
We analyze nonparametric estimators for the distribution function and density in the singly and doubly interval censoring model. The classical approach is to use parametric families like Weibull, log-normal or gamma in the estimation procedure. We propose nonparametric estimates which are also capable of catching finer aspects of the density, like multimodality, in contrast with the classical parametric methods. We apply this to the estimation of the density of the incubation time distribution of COVID-19. R scripts are provided for the nonparametric methods.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2021 program
|
