A probabilistic procedure for quantifying the relative importance of model inputs characterized by second-order probability models

DOI10.1016/j.ijar.2018.04.007zbMath1451.62061OpenAlexW2802919989WikidataQ129928637 ScholiaQ129928637MaRDI QIDQ1644897

Zuotao Wang, Fuchao Liu, Pengfei Wei, Zhen-Zhou Lü

Publication date: 22 June 2018

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2018.04.007

zbMATH Keywords

Krigingrelative importanceSobol' indicesextended Monte Carlo simulationsecond-order probability model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Monte Carlo methods (65C05)

Related Items (2)

Measuring regional effects of model inputs with random Forest ⋮ A novel sensitivity index for analyzing the response of numerical models with interval inputs

Uses Software

• DACE

Cites Work

• Sensitivity analysis: a review of recent advances
• Understanding and comparisons of different sampling approaches for the Fourier amplitudes sensitivity test (FAST)
• Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
• Regression and Kriging metamodels with their experimental designs in simulation: a review
• An application of the kriging method in global sensitivity analysis with parameter uncertainty
• A generalized separation for the variance contributions of input variables and their distribution parameters
• Borgonovo moment independent global sensitivity analysis by Gaussian radial basis function meta-model
• Uniformly distributed sequences with an additional uniform property
• Better estimation of small sobol' sensitivity indices
• Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach
• Transformations and Invariance in the Sensitivity Analysis of Computer Experiments
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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