Projection pursuit emulation for many-input computer experiments

This paper studies projection pursuit emulation for computer experiments with many input variables. This method aims at capturing the most influential directions of the inputs to the response, and thus the active dimensionality is reduced. Its interpolation property is proved under certain conditions. We also propose a two-stage method to handle the case where the projection pursuit method does not converge. Simulation studies show that the proposed methods are more efficient than the traditional Kriging methods.

Automated summary

This paper investigates projection pursuit emulation for computer experiments with multiple input variables. The method aims to capture the most influential input directions to reduce active dimensionality. Its interpolation property is proven under specific conditions, and a two-stage method is proposed to handle situations where the projection pursuit method fails to converge. Simulation studies demonstrate that the proposed methods are more efficient than traditional Kriging methods.