Computationally Efficient Use of Derivatives in Emulation of Complex Computational Models
Conference
·
OSTI ID:1043495
- Los Alamos National Laboratory
- University of Wyoming
We will investigate the use of derivative information in complex computer model emulation when the correlation function is of the compactly supported Bohman class. To this end, a Gaussian process model similar to that used by Kaufman et al. (2011) is extended to a situation where first partial derivatives in each dimension are calculated at each input site (i.e. using gradients). A simulation study in the ten-dimensional case is conducted to assess the utility of the Bohman correlation function against strictly positive correlation functions when a high degree of sparsity is induced.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- DOE/LANL
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1043495
- Report Number(s):
- LA-UR-12-22020; TRN: US201214%%50
- Resource Relation:
- Conference: IMS/ASA Spring Research Conference 2012 ; 2012-06-13 - 2012-06-15 ; Cambridge, Massachusetts, United States
- Country of Publication:
- United States
- Language:
- English
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