Salib contains python implementations of commonly used global sensitivity analysis methods, including sobol sobol 2001, andrea saltelli 2002, andrea saltelli et al. An opensource python library for sensitivity analysis. Sample matrix for uncertainty and sensitivity analysis each row is a sample trial for one model run. Complex mathematical and computational models are used in all. For this definition of sensitivity analysis to be of use, it must first be made clear what is meant here by model, numerical or otherwise, as well as by the terms input and output which will be used throughout this book. Sensitivity analysis provides users of mathematical and simulation models with tools to appreciate the dependency of the model output from model input, and to investigate how important is each model input in determining its output. Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters. Useful in systems modeling to calculate the effects of model inputs or exogenous factors on outputs of interest. Salib is useful in simula tion, optimisation and systems modelling to calculate the influence of model inputs or. This is an important method for checking the quality of a given model, as well as a powerful tool for checking the robustness and reliability of its analysis. Parametric sensitivity analysis sa is an essential tool in optical data analysis aiming to quantify the relative importance of optical model parameters and identify those with a low influence.
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