Computationally Efficient Use of Derivatives in Emulation of Complex Computational Models

Conference · Thu Jun 07 04:00:00 EDT 2012

OSTI ID:1043495

Williams, Brian J ^[1]; Marcy, Peter W ^[2]

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1. Los Alamos National Laboratory
2. 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)
• Sponsoring Organization: DOE/LANL
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 1043495
• Report Number(s): LA-UR-12-22020
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
COMPUTERIZED SIMULATION
CORRELATION FUNCTIONS
GAUSSIAN PROCESSES
MANY-DIMENSIONAL CALCULATIONS
MEETINGS
USES