Development of an Agent-Based Model (ABM) to Simulate the Immune System and Integration of a Regression Method to Estimate the Key ABM Parameters by Fitting the Experimental Data
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DOI: 10.1371/journal.pone.0141295
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- Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.
- Hongyu Miao & Hulin Wu & Hongqi Xue, 2014. "Generalized Ordinary Differential Equation Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1672-1682, December.
- Hongyu Miao & Carrie Dykes & Lisa M. Demeter & Hulin Wu, 2009. "Differential Equation Modeling of HIV Viral Fitness Experiments: Model Identification, Model Selection, and Multimodel Inference," Biometrics, The International Biometric Society, vol. 65(1), pages 292-300, March.
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