Numerical study of discretization algorithms for stable estimation of disease parameters and epidemic forecasting
In this paper we investigate how various discretization schemes could be incorporated in regularization algorithms for stable parameter estimation and forecasting in epidemiology. Specifically, we compare parametric and nonparametric discretization tools in terms of their impact on the accuracy of r...
Main Authors: | Aurelie Akossi, Gerardo Chowell-Puente, Alexandra Smirnova |
---|---|
Format: | Article |
Language: | English |
Published: |
AIMS Press
2019-04-01
|
Series: | Mathematical Biosciences and Engineering |
Subjects: | |
Online Access: | https://www.aimspress.com/article/10.3934/mbe.2019182?viewType=HTML |
Similar Items
-
Systematic comparison of epidemic growth patterns using two different estimation approaches
by: Yiseul Lee, et al.
Published: (2021-01-01) -
A primer on stable parameter estimation and forecasting in epidemiology by a problem-oriented regularized least squares algorithm
by: Alexandra Smirnova, et al.
Published: (2017-05-01) -
Discrete time forecasting of epidemics
by: Daniel A.M. Villela
Published: (2020-01-01) -
Ensemble bootstrap methodology for forecasting dynamic growth processes using differential equations: application to epidemic outbreaks
by: Gerardo Chowell, et al.
Published: (2021-02-01) -
Constrained and regularized system identification
by: Tor A. Johansen
Published: (1998-04-01)