Projection pursuit emulation for many-input computer experiments

DOI10.1080/03610926.2020.1853772OpenAlexW3111518526MaRDI QIDQ5095994

Yunfei Wei, Shifeng Xiong, Daijun Chen

Publication date: 12 August 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2020.1853772

zbMATH Keywords

interpolationGaussian processKrigingnonparametric regression model

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• gss
• lhs
• mlegp
• NLopt

Cites Work

• Unnamed Item
• Multi-Resolution Functional ANOVA for Large-Scale, Many-Input Computer Experiments
• Exploratory designs for computational experiments
• Variable bandwidth and local linear regression smoothers
• Moderate projection pursuit regression for multivariate response data
• Projection pursuit regression for moderate nonlinearities
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• The design and analysis of computer experiments
• Optimal smoothing in single-index models
• Local linear regression smoothers and their minimax efficiencies
• Functional projection pursuit regression
• Kernel Approximation: From Regression to Interpolation
• A Gaussian process regression approach to a single-index model
• Interpolation Methods for Adapting to Sparse Design in Nonparametric Regression
• Dimension Reduction for Gaussian Process Emulation: An Application to the Influence of Bathymetry on Tsunami Heights
• A Semiparametric Approach to Dimension Reduction
• Variable selection via a multi-stage strategy

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