Analytical HDMR formulas for functions expressed as quadratic polynomials with a multivariate normal distribution

DOI10.1007/s10910-014-0365-6zbMath1395.62211OpenAlexW2068370958MaRDI QIDQ460960

Herschel Rabitz, Genyuan Li

Publication date: 9 October 2014

Published in: Journal of Mathematical Chemistry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10910-014-0365-6

zbMATH Keywords

sensitivity analysiscorrelated variablesHigh Dimensional Model Representation (HDMR)

Mathematics Subject Classification ID

Analysis of variance and covariance (ANOVA) (62J10)

Related Items (2)

Sparse and nonnegative sparse D-MORPH regression ⋮ High dimensional model representation constructed by support vector regression. I. Independent variables with known probability distributions

Cites Work

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• General formulation of HDMR component functions with independent and correlated variables
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• D-MORPH regression: Application to modeling with unknown parameters more than observation data
• General foundations of high-dimensional model representations
• Estimation of global sensitivity indices for models with dependent variables
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• On the Relative Importance of Input Factors in Mathematical Models
• A Class of Statistics with Asymptotically Normal Distribution
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
• Efficient implementation of high dimensional model representations
• High dimensional model representations generated from low dimensional data samples. I: mp-cut-HDMR

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