Author: Smirnova, Alexandra; Chowell, Gerardo
Title: A primer on stable parameter estimation and forecasting in epidemiology by a problem-oriented regularized least squares algorithm Document date: 2017_5_25
ID: 3fwla5ox_34
Snippet: In conclusion, we have illustrated the potential of rigorous mathematical approaches for generating reliable parameter estimates and useful epidemic forecasts in the context of the generalized Richards equation, a simple phenomenological 4parameter model. Our results here suggest that carefully linking mathematical models with regularization techniques could lead to stable parameter estimation and associated forward projections. Fig. 5 . Liberia:.....
Document: In conclusion, we have illustrated the potential of rigorous mathematical approaches for generating reliable parameter estimates and useful epidemic forecasts in the context of the generalized Richards equation, a simple phenomenological 4parameter model. Our results here suggest that carefully linking mathematical models with regularization techniques could lead to stable parameter estimation and associated forward projections. Fig. 5 . Liberia: Estimation of r, t, p, a, and K, and Forecasting. r ¼ 0.12(95% CI: 0.63, 1.9), t ¼ 15(95% CI: 13, 17), p ¼ 0.82 (95% CI: 0.7, 0.88), a ¼ 1 (95% CI: 1, 1.04), K ¼ 3.5 ,10 3 (95% CI: 2.2 ,10 3 , 4.4 ,10 3 ).
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