تقرير
Comparative Analysis of Practical Identifiability Methods for an SEIR Model
| العنوان: | Comparative Analysis of Practical Identifiability Methods for an SEIR Model |
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| المؤلفون: | Saucedo, Omar, Laubmeier, Amanda, Tang, Tingting, Levy, Benjamin, Asik, Lale, Pollington, Tim, Prosper, Olivia |
| سنة النشر: | 2024 |
| المجموعة: | Quantitative Biology Statistics |
| مصطلحات موضوعية: | Statistics - Methodology, Quantitative Biology - Populations and Evolution, Quantitative Biology - Quantitative Methods |
| الوصف: | Identifiability of a mathematical model plays a crucial role in parameterization of the model. In this study, we establish the structural identifiability of a Susceptible-Exposed-Infected-Recovered (SEIR) model given different combinations of input data and investigate practical identifiability with respect to different observable data, data frequency, and noise distributions. The practical identifiability is explored by both Monte Carlo simulations and a Correlation Matrix approach. Our results show that practical identifiability benefits from higher data frequency and data from the peak of an outbreak. The incidence data gives the best practical identifiability results compared to prevalence and cumulative data. In addition, we compare and distinguish the practical identifiability by Monte Carlo simulations and a Correlation Matrix approach, providing insights for when to use which method for other applications. Comment: Minor changes to clarify why structural identifiability with respect to incidence data was not perform |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2401.15076 |
| رقم الأكسشن: | edsarx.2401.15076 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |