Dealing with Measurement Uncertainties as Nuisance Parameters in Bayesian Model Calibration

DOI10.1137/19M1283707zbMath1454.62100MaRDI QIDQ5139352

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Publication date: 8 December 2020

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

zbMATH Keywords

regularizationinverse problemsBayesian statisticsmodel calibrationshrinkage priorsoverfittingmeasurement uncertaintymoment penalization

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Parametric inference under constraints (62F30) Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30)

Related Items (1)

Fast matrix algebra for Bayesian model calibration

Cites Work

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• Efficient calibration for imperfect computer models
• Dynamic Bayesian influenza forecasting in the United States with hierarchical discrepancy (with discussion)
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• Bayesian Calibration of Computer Models
• Learning about physical parameters: the importance of model discrepancy
• Computer Model Calibration Using High-Dimensional Output
• Dirichlet–Laplace Priors for Optimal Shrinkage

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