Analytic uncertainty and sensitivity analysis of models with input correlations

作者：Zhu, Yueying^*; Wang, Qiuping A.; Li, Wei; Cai, Xu

来源：Physica A: Statistical Mechanics and Its Applications , 2018, 494: 140-162.

DOI：10.1016/j.physa.2017.12.041

• Uncertainty analysis
• Sensitivity index
• Correlation
• Covariance
• HIV model

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

• 出版日期2018-3-15
• 单位华中师范大学