Abstract:

Computer experiments introduce the fundamental idea of building a metamodel of its simulation model, which has widely used for complex physical systems. The paper proposes a novel Bayesian meta modeling approach for computer experiments. It imposes a hierarchical prior on the correlation parameters in Kriging based on Jeffreys’noninformative hyper prior, and is solved by the expectation maximization (EM) algorithm. Though the new approach is essentially a penalized likelihood method, it does not involve any parameters to be adjusted or estimated. Compared with several other methods in literature, experimental results show that the new approach not only yields state of the art performance, but also has much low computational cost.