gra2004-04

Adaptive exploration of computer experiment parameter spaces

by:
Robert B. Gramacy, Herbert K. H. Lee, William Macready

ABSTRACT

Many complex phenomena are difficult to investigate directly through controlled experiments. Instead, computer simulation is becoming a commonplace alternative to providing insight into such phenomena. The drive towards higher fidelity simulation continues to tax the fastest of computers, even in highly distributed computing environments. Computational fluid dynamics simulations in which fluid flow phenomena are modeled are an excellent example---fluid flows over complex surfaces may be modeled accurately but only at the cost of supercomputer resources. In this article, we discuss the problem of fitting a response surface for a computer model when we also have the ability to design the experiment adaptively, updating the experiment as we learn about the model-- a task to which we feel the Bayesian approach is particularly well-suited. An extended version of this paper, highlighting computation and implementation details, was one of four winners of the 2005 ASA (American Statistical Association) Section on Statistical Computing and Statistical Graphics Student paper competition.

BIBTEX

@TECHREPORT{gra2004:isba,       Author = {Robert B. Gramacy and Herbert K. H. Lee and William Macready},       Institution = {Bulletin of the International Society for Bayeaian Analysis (ISBA)},       Title = {Adaptive exploration of computer experiment parameter spaces},       Year = {2004},       Month = {December},       Url = {http://www.ams.ucsc.edu/~rbgramacy/papers/gra2004-04.pdf}       }

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