Analytical HDMR formulas for functions expressed as quadratic polynomials with a multivariate normal distribution.
- Resource Type
- Article
- Authors
- Li, Genyuan; Rabitz, Herschel
- Source
- Journal of Mathematical Chemistry. Sep2014, Vol. 52 Issue 8, p2052-2073. 22p.
- Subject
- *HIGH-dimensional model representation
*POLYNOMIALS
*QUADRATIC equations
*GAUSSIAN distribution
*MULTIVARIATE analysis
*MATHEMATICAL functions
- Language
- ISSN
- 0259-9791
High Dimensional Model Representation (HDMR) is a general set of quantitative model assessment and analysis tools for systems with many variables. A general formulation for the HDMR component functions with independent and correlated variables was obtained previously. Since the HDMR component functions generally are coupled to one another and involve multi-dimensional integrals, explicit formulas for the component functions are not available for an arbitrary function with an arbitrary probability distribution amongst their variables. This paper presents analytical formulas for the HDMR component functions and the corresponding sensitivity indexes for the common case of a function expressed as a quadratic polynomial with a multivariate normal distribution over its variables. This advance is important for practical applications of HDMR with correlated variables. [ABSTRACT FROM AUTHOR]