Uncertainty and Sensitivity Analyses Methods for Agent-Based Mathematical Models: An Introductory Review
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This introductory review discusses origins, conventions, implementation and result interpretation of three uncertainty and sensitivity analyses methods, suitable to use when working with agent-based models, namely Consistency Analysis, Robustness Analysis and Latin Hypercube Analysis.Abstract:
Multiscale, agent-based mathematical models of biological systems are often associated with model uncertainty and sensitivity to parameter perturbations. Here, three uncertainty and sensitivity analyses methods, that are suitable to use when working with agent-based models, are discussed. These methods are namely Consistency Analysis, Robustness Analysis and Latin Hypercube Analysis. This introductory review discusses origins, conventions, implementation and result interpretation of the aforementioned methods. Information on how to implement the discussed methods in MATLAB is included.read more
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