Estimation and model errors in Gaussian-process-based sensitivity analysis of multidimensional outputs
Global sensitivity analysis (GSA) of models with multidimensional outputs is usually performed by combining statistical techniques, such as basis expansions, metamodeling and sampling- based estimation of sensitivity indices. By neglecting truncation error from basis expansion, two main sources of errors propagate to t...