Sensitivity analysis of computer models can typically require a large number of model runs. When these models are
computationally expensive to run, it may be advantageous to invest in computationally cheaper surrogate models (emulators or
meta-models) that can provide almost the same output as the original model and estimate the sensitivity indices for each input. In
this abstract the MARS method is used to mimic the behavior of a nonlinear and non-additive test function. The results show that,
overall, MARS provides acceptable estimates of total sensitivity indices at a much lower cost than using only runs of the original
model.
SHAHSAVANI Davood;
TARANTOLA Stefano;
RATTO Marco;
2011-03-21
Elsevier
JRC62993
1877-0428,
https://publications.jrc.ec.europa.eu/repository/handle/JRC62993,
10.1016/j.sbspro.2010.05.204,
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