Projection pursuit emulation for many-input computer experiments

Abstract

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.

Keywords:

• Gaussian process
• interpolation
• Kriging
• nonparametric regression model

Acknowledgments

We thank the referees for helpful suggestions.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 11671386, 11871033).