A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models
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Publication:6109971
DOI10.1080/01621459.2021.1956938arXiv2107.08288OpenAlexW3194928046MaRDI QIDQ6109971
Yu Ding, Shiyuan He, Jianhua Z. Huang, Rui Tuo, Arash Pourhabib
Publication date: 4 July 2023
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2107.08288
smoothing splinesreproducing kernel Hilbert spacescalibrationuncertainty quantificationcomputer experiment
Cites Work
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- Scaled Gaussian Stochastic Process for Computer Model Calibration and Prediction
- Efficient calibration for imperfect computer models
- Calibrating a large computer experiment simulating radiative shock hydrodynamics
- Convergence rates for multivariate smoothing spline functions
- Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
- Interpolation of spatial data. Some theory for kriging
- The design and analysis of computer experiments.
- Optimal global rates of convergence for nonparametric regression
- The covering number in learning theory
- Effective model calibration via sensible variable identification and adjustment with application to composite fuselage simulation
- Computer model validation with functional output
- Estimates in Besov spaces for transport and transport-diffusion equations with almost Lipschitz coefficients
- Bayesian Calibration of Computer Models
- Computer Model Calibration Using High-Dimensional Output
- A Tool for the Analysis of Quasi-Newton Methods with Application to Unconstrained Minimization
- Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
- Nonparametric functional calibration of computer models
- Combining Field Data and Computer Simulations for Calibration and Prediction
- Computer Model Calibration with Confidence and Consistency
- Adjustments to Computer Models via Projected Kernel Calibration
- A Frequentist Approach to Computer Model Calibration
- A Theoretical Framework for Calibration in Computer Models: Parametrization, Estimation and Convergence Properties
- Bayesian Projected Calibration of Computer Models
- Scattered Data Approximation
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