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Matlab Toolbox for uncertainty analysis, sensitivity analysis, parameter estimation, and confidence subcontour box estimation for Mathematical models implemented with Symbolic Math Toolbox or Simulink

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GSUA-CSB

Global Sensitivity and Uncertainty Analysis - Confidence Subcontour Box (GSUA-CSB) Toolbox is a product developed by Universidad EAFIT for command-line mathematical model validation in both of Simulink or Symbolic Math Toolbox environment . At present time, the toolbox allows to perform the following functions: To apply and visualize several variance-based sensitivity (SA) and uncertainty (UA) analysis, to estimate model parameters (PE) and to estimate confidence subcontour box (CSB) for estimated parameters. This toolbox is based on the previous work of Carlos Mario Vélez: GSUA of dynamical systems using variance-based methods.

Sensitivity indices estimators implemented in this toolbox are based on the following works:

[1]: Saltelli, A., Annoni, P., Azzini, I., Campolongo, F., Ratto, M., and Tarantola, S. (2010). Variance based sensitivity analysis of model output. design and estimator for the total sensitivity index. Computer Physics Communications, 181(2):259–270.

[2]: Xiao, S., Lu, Z., and Wang, P. (2018). Multivariate global sensitivity analysis based on distance components decomposition. Risk Analysis, 38(12):2703–2721.

Cite this work as: Rojas-Díaz, Daniel and Vélez-Sánchez, Carlos Mario (2019). GSUA-CSB (https://www.github.com/drojasd/GSUA-CSB), GitHub. Retrieved September 2, 2019. doi:10.5755281/zenodo.3383316.

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CSB method in detail

Working paper for CSB method available: A NOVEL ALGORITHM FOR CONFIDENCE SUBCONTOUR BOX (CSB) ESTIMATION: AN ALTERNATIVE TO TRADITIONAL CONFIDENCE INTERVALS

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Matlab Toolbox for uncertainty analysis, sensitivity analysis, parameter estimation, and confidence subcontour box estimation for Mathematical models implemented with Symbolic Math Toolbox or Simulink

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