a review on global sensitivity analysis methods


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PDF Evaluation of global sensitivity analysis methods for computational

Iooss B and Lemaоtre P (2015) A review on global sensitivity analysis methods Evaluation of global sensitivity analysis methods for computational structural 

  • What are sensitivity analysis methods?

    Sensitivity analysis is a financial model that determines how target variables are affected based on changes in other variables known as input variables.
    It is a way to predict the outcome of a decision given a certain range of variables.

  • What are the methods of global sensitivity analysis?

    There are many global sensitivity analysis methods including the Sobol's sensitivity estimates, the Fourier amplitude sensitivity test (FAST), and the Monte-Carlo-based regression–correlation indices.

  • Which tool is best for sensitivity analysis?

    Tornado diagrams and spider diagrams are graphical tools that can help visualize the sensitivity and uncertainty of the decision problem, and compare the alternatives based on their sensitivity and robustness.

  • For global sensitivity analysis, Morris method requires the smallest number of sample points and can be used to get a preliminary and qualitative knowledge on sensitivity information.
    Regression-based methods (e.g., PRCC) can be applied to the cases where the output is monotonically related to the input.

Three kinds of methods are distinguished: the screening (coarse sorting of the most influential inputs among a large number), the measures of importance (quantitative sensitivity indices) and the deep exploration of the model behaviour (measuring the effects of inputs on their all variation range).
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