SALib: An open-source Python library for Sensitivity Analysis

SALib: An open-source Python library for Sensitivity Analysis

2017 | Jon Herman1 and Will Usher2
SALib is an open-source Python library designed for sensitivity analysis, offering implementations of various global sensitivity analysis methods. These methods include Sobol, Morris, FAST, Delta Moment-Independent Measure, Derivative-based Global Sensitivity Measure (DGSM), and Fractional Factorial Sensitivity Analysis. SALib simplifies the process of implementing these techniques in simulation, optimization, and systems modeling by providing functions to generate samples from model inputs, analyze model outputs, and visualize results. The library is useful for researchers and modellers who need to understand the impact of input variables on model outputs.SALib is an open-source Python library designed for sensitivity analysis, offering implementations of various global sensitivity analysis methods. These methods include Sobol, Morris, FAST, Delta Moment-Independent Measure, Derivative-based Global Sensitivity Measure (DGSM), and Fractional Factorial Sensitivity Analysis. SALib simplifies the process of implementing these techniques in simulation, optimization, and systems modeling by providing functions to generate samples from model inputs, analyze model outputs, and visualize results. The library is useful for researchers and modellers who need to understand the impact of input variables on model outputs.
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