Correlation method for variance reduction of Monte Carlo integration in RS-HDMR
Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 277-283, 2003
| Veröffentlicht in: | Journal of computational chemistry. - 1984. - 24(2003), 3 vom: 15. Feb., Seite 277-83 |
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| Weitere Verfasser: | , , |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2003
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| Zugriff auf das übergeordnete Werk: | Journal of computational chemistry |
| Schlagworte: | Journal Article |
| Zusammenfassung: | Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 277-283, 2003 The High Dimensional Model Representation (HDMR) technique is a procedure for efficiently representing high-dimensional functions. A practical form of the technique, RS-HDMR, is based on randomly sampling the overall function and utilizing orthonormal polynomial expansions. The determination of expansion coefficients employs Monte Carlo integration, which controls the accuracy of RS-HDMR expansions. In this article, a correlation method is used to reduce the Monte Carlo integration error. The determination of the expansion coefficients becomes an iteration procedure, and the resultant RS-HDMR expansion has much better accuracy than that achieved by direct Monte Carlo integration. For an illustration in four dimensions a few hundred random samples are sufficient to construct an RS-HDMR expansion by the correlation method with an accuracy comparable to that obtained by direct Monte Carlo integration with thousands of samples |
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| Beschreibung: | Date Completed 07.07.2003 Date Revised 04.11.2003 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1096-987X |