Predictive Subdata Selection for Computer Models

DOI10.1080/10618600.2022.2097247OpenAlexW4284887052MaRDI QIDQ6094090

Ming Chung Chang

Publication date: 9 October 2023

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://figshare.com/articles/dataset/Predictive_Subdata_Selection_for_Computer_Models/20263820

zbMATH Keywords

data reductioncomputer experimentsmassive/big datanumerosity reductionsupervised subsampling

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Bagging predictors
• Multi-Resolution Functional ANOVA for Large-Scale, Many-Input Computer Experiments
• Energy statistics: a class of statistics based on distances
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• Heat transfer modeling in data centers
• Efficient global optimization of expensive black-box functions
• Handbook of big data analytics
• The design and analysis of computer experiments
• Signal aliasing in Gaussian random fields for experiments with qualitative factors
• Principles of experimental design for big data analysis
• Composite Gaussian process models for emulating expensive functions
• Support points
• Orthogonal subsampling for big data linear regression
• Experiments
• Variable Selection for Gaussian Process Models using Experimental Design-Based Subagging
• Exploiting Variance Reduction Potential in Local Gaussian Process Search
• More efficient approximation of smoothing splines via space-filling basis selection
• Information-Based Optimal Subdata Selection for Big Data Linear Regression

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