Global Sensitivity Analysis for Statistical Model Parameters

@article{Hart2019GlobalSA,
  title={Global Sensitivity Analysis for Statistical Model Parameters},
  author={J. Hart and J. Bessac and E. Constantinescu},
  journal={SIAM/ASA J. Uncertain. Quantification},
  year={2019},
  volume={7},
  pages={67-92}
}
Global sensitivity analysis (GSA) is frequently used to analyze the influence of uncertain parameters in mathematical models. In principle, tools from GSA may be extended to analyze the influence of parameters in statistical models. Such analyses may enable parsimonious modeling and greater predictive capability. However, difficulties such as parameter correlation, model stochasticity, and multivariate model output prohibit a direct extension of GSA tools to statistical models. We introduce a… Expand
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