Learning Global Sensitivity Indices from Observational Data: A Metamodel-Based Approach

arXiv:2609.40342 · stat.ME, stat.ML · Submitted 2026-09-30 · Read on arXiv

stat.ME, stat.ML

Submitted: 2026-09-30

Updated: 2026-09-30

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 21× in this paper · explained in 2 episodes
• Consistency — 15× in this paper · explained in 3 episodes
• Global Sensitivity Analysis — 11× in this paper
• Random Forests — 7× in this paper
• Redundancy — 4× in this paper · explained in 2 episodes
• Model-Agnostic — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Loss Function — 2× in this paper · explained in 2 episodes
• Neural Networks — 2× in this paper
• Robustness — 2× in this paper · explained in 5 episodes
• Uncertainty Quantification — 2× in this paper · explained in 8 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• National Health and Nutrition Examination Survey — 1× in this paper

Sources

• Generalized Functional ANOVA: A Complete Theoretical Framework

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