Empirical Bayesian Analysis for High-Dimensional Computer Output

This article proposes a two-stage statistical method for the analysis of multivariate computer experiments when at least one of the output dimensions is large. The stage-one data are modeled by a multivariate extension of a widely used scalar statistical model for computer output. Conditioned on stage-one data, a simple statistical model is then proposed for the stage-two data. The method is demonstrated in a geophysical application involving an ocean model.