SAFE Toolbox

The SAFE Toolbox provides a set of functions to perform Global Sensitivity Analysis in Matlab/Octave environment. It implements several methods, including the Elementary Effects Test, Regional Sensitivity Analysis, Variance-Based (Sobol’) sensitivity analysis and the novel PAWN method.

Keywords for this software

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References in zbMATH (referenced in 10 articles )

Showing results 1 to 10 of 10.
Sorted by year (citations)

  1. Arnald Puy, Samuele Lo Piano, Andrea Saltelli, Simon A. Levin: sensobol: an R package to compute variance-based sensitivity indices (2021) arXiv
  2. Bhattacharyya, Biswarup: Global sensitivity analysis: a Bayesian learning based polynomial chaos approach (2020)
  3. Qian, George; Mahdi, Adam: Sensitivity analysis methods in the biomedical sciences (2020)
  4. Xiao, Sinan; Oladyshkin, Sergey; Nowak, Wolfgang: Forward-reverse switch between density-based and regional sensitivity analysis (2020)
  5. Jain, Harsh; Jackson, Trachette: Mathematical modeling of cellular cross-talk between endothelial and tumor cells highlights counterintuitive effects of VEGF-targeted therapies (2018)
  6. Joshi, Tejas; Elderd, Bret D.; Abbott, Karen C.: No appendix necessary: fecal transplants and antibiotics can resolve \textitClostridiumdifficile infection (2018)
  7. Kasia Sawicka, Gerard B.M. Heuvelink, Dennis J.J. Walvoort: Spatial Uncertainty Propagation Analysis with the spup R Package (2018) not zbMATH
  8. Zhuge, Chengxiang; Shao, Chunfu: Agent-based modelling of locating public transport facilities for conventional and electric vehicles (2018)
  9. Harry Zekollari: TopoZeko: A MATLAB function for 3-D and 4-D topographical visualization in geosciences (2017) not zbMATH
  10. Goulet, D.: Modeling, simulating, and parameter Fitting of biochemical kinetic experiments (2016)