A new methodology based on covariance and HDMR for global sensitivity analysis

DOI10.1016/j.apm.2015.01.011zbMath1443.62007OpenAlexW2042187519MaRDI QIDQ2282642

Guancheng Fang, Lei Cheng, Zhen-Zhou Lü

Publication date: 8 January 2020

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2015.01.011

zbMATH Keywords

sensitivity analysiscovariancecomputing efficiencyhigh-dimensional model representation (HDMR)

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Linear inference, regression (62J99)

Related Items (3)

A generalized sensitivity analysis method based on variance and covariance decomposition of summatory functions for multi-input multi-output systems ⋮ A non-probabilistic methodology for reliable sustainability planning: an application to the Iraqi national irrigation system ⋮ Improved Moving Least Square-Based Multiple Dimension Decomposition (MDD) Technique for Structural Reliability Analysis

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Moving least squares based sensitivity analysis for models with dependent variables
• Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
• Moment-independent importance measure of basic random variable and its probability density evolution solution
• Making best use of model evaluations to compute sensitivity indices
• Analysis of variance designs for model output
• Nonparametric estimation of global functionals and a measure of the explanatory power of covariates in regression
• Importance analysis for models with correlated input variables by the state dependent parameters method
• Asymptotic normality and efficiency of two Sobol index estimators
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

This page was built for publication: A new methodology based on covariance and HDMR for global sensitivity analysis