Abstract
This paper presents recently developed Enhanced Multivariance Product Representation (EMPR) method for multivariate functions. EMPR disintegrates a multivariate function to components which are respectively constant, univariate, bivariate and so on in ascending multivariance. Although the EMPR method has the same philosophy with the High Dimensional Model Representation (HDMR) method, it has been proposed to get better quality than HDMR's with the help of the support functions. For this purpose, we investigate the EMPR truncation qualities with respect to the selection of the support functions. The obtained results and a number of numerical implementations to show the efficiency of the method are also given in this paper.
| Original language | English |
|---|---|
| Pages (from-to) | 827-840 |
| Number of pages | 14 |
| Journal | Journal of Mathematical Chemistry |
| Volume | 48 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2010 |
Keywords
- Approximation
- High dimensional model representation
- Multivariate functions
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