A Bayesian approach to the design and analysis of computer experiments

Technical Report · Thu Sep 01 00:00:00 EDT 1988

OSTI ID:6734087

Currin, C; Mitchell, T; Morris, M; Ylvisaker, D

We consider the problem of designing and analyzing experiments for prediction of the function y(t), telement ofT, where y is evaluated by means of a computer code (typically by solving complicated equations that model a physical system), and T represents the domain of inputs to the code. We use a Bayesian approach, in which uncertainty about y is represented by a spatial stochastic process (random function); here we restrict attention to stationary Gaussian processes. The posterior mean function can be used as an interpolating function, with uncertainties given by the posterior standard deviations. Instead of completely specifying the prior process, we consider several families of priors, and suggest some cross-validational methods for choosing one that performs relatively well on the function at hand. As a design criterion, we use the expected reduction in the entropy of the random vector y(T*), where T*is contained inT is a given finite set of ''sites'' (input configurations) at which predictions are to be made. We describe an exchange algorithm for constructing designs that are optimal with respect to this criterion. To demonstrate the use of these design and analysis methods, several examples are given, including one experiment on a computer model of a thermal energy storage device and another on an integrated circuit simulator. 23 refs., 14 figs., 1 tab.

• Research Organization: Oak Ridge National Lab., TN (USA)
• DOE Contract Number: AC05-84OR21400
• OSTI ID: 6734087
• Report Number(s): ORNL-6498; ON: DE89001949
• Resource Relation: Other Information: Portions of this document are illegible in microfiche products
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
COMPUTERIZED SIMULATION
ALGORITHMS
COMPUTER ARCHITECTURE
COMPUTER GRAPHICS
COMPUTER-AIDED DESIGN
CORRELATION FUNCTIONS
INTEGRATED CIRCUITS
MATHEMATICAL MODELS
STOCHASTIC PROCESSES
THERMAL ENERGY STORAGE EQUIPMENT
ELECTRONIC CIRCUITS
EQUIPMENT
FUNCTIONS
MATHEMATICAL LOGIC
MICROELECTRONIC CIRCUITS
SIMULATION
990210* - Supercomputers- (1987-1989)