Decomposing Functional Model Inputs for Variance-Based Sensitivity Analysis

DOI10.1137/18M1173058zbMath1409.62147WikidataQ128950728 ScholiaQ128950728MaRDI QIDQ4611528

Max D. Morris

Publication date: 21 January 2019

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

zbMATH Keywords

Gaussian processesPoisson processuncertainty analysiscomputer experimentsSobol' indicesvariance propagation

Mathematics Subject Classification ID

Gaussian processes (60G15) Monte Carlo methods (65C05) Analysis of variance and covariance (ANOVA) (62J10)

Cites Work

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• Making best use of model evaluations to compute sensitivity indices
• Better estimation of small sobol' sensitivity indices
• A Class of Statistics with Asymptotically Normal Distribution
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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