Add to ORKGSobol' sensitivity indeices, used in variance based global sensitivity analysis of model output, are compared with the analysis of variance in classical factorial design. Monte Carlo computation of Sobol' indices is described briefly, and a bootstrap approach is presented, which can be used to produce a confidence interval for the true, unknown indices.JRC.(EI)-Environment Institut
International audienceThis paper deals with global sensitivity analysis of computer model output. Gi...
In global sensitivity analysis, the well-known Sobol’ sensitivity indices aim to quantify how the va...
The variance-based method of global sensitivity analysis based on Sobol' sensitivity indices has bec...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity...
International audienceMany mathematical models involve input parameters, which are not precisely kno...
The variance-based method of global sensitivity indices based on Sobol' sensitivity indices became v...
Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific ap...
Sensitivity analysis assesses the influence of input parameters on the conclusion of a model. Tradit...
Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific ap...
A novel approach to estimate variance based sensitivity indices for the case of correlated variables...
This chapter makes a review, in a complete methodological framework, of various global sensitivity a...
Sensitivity analysis involves determining the contribution of individual input factors to uncertaint...
Variance based methods have assessed themselves as versatile and effective among the various availa...
The estimation of variance-based importance measures (called Sobol' indices) of the input variables ...
A novel theoretical and numerical framework for the estimation of Sobol sensitivity indices for mode...
International audienceThis paper deals with global sensitivity analysis of computer model output. Gi...
In global sensitivity analysis, the well-known Sobol’ sensitivity indices aim to quantify how the va...
The variance-based method of global sensitivity analysis based on Sobol' sensitivity indices has bec...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity...
International audienceMany mathematical models involve input parameters, which are not precisely kno...
The variance-based method of global sensitivity indices based on Sobol' sensitivity indices became v...
Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific ap...
Sensitivity analysis assesses the influence of input parameters on the conclusion of a model. Tradit...
Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific ap...
A novel approach to estimate variance based sensitivity indices for the case of correlated variables...
This chapter makes a review, in a complete methodological framework, of various global sensitivity a...
Sensitivity analysis involves determining the contribution of individual input factors to uncertaint...
Variance based methods have assessed themselves as versatile and effective among the various availa...
The estimation of variance-based importance measures (called Sobol' indices) of the input variables ...
A novel theoretical and numerical framework for the estimation of Sobol sensitivity indices for mode...
International audienceThis paper deals with global sensitivity analysis of computer model output. Gi...
In global sensitivity analysis, the well-known Sobol’ sensitivity indices aim to quantify how the va...
The variance-based method of global sensitivity analysis based on Sobol' sensitivity indices has bec...