Semi-parametric adjustment to computer models
From MaRDI portal
Publication:4987231
DOI10.1080/02331888.2020.1862113zbMath1472.62040OpenAlexW3110983140MaRDI QIDQ4987231
Publication date: 29 April 2021
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888.2020.1862113
Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30) Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) (46E22)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A better understanding of model updating strategies in validating engineering models
- Efficient calibration for imperfect computer models
- Weak convergence and empirical processes. With applications to statistics
- Computer model validation with functional output
- Bayesian Calibration of Computer Models
- Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
- An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels
- Bayesian Forecasting for Complex Systems Using Computer Simulators
- Asymptotic Statistics
- Prediction based on the Kennedy-O’Hagan calibration model: asymptotic consistency and other properties
- Combining Field Data and Computer Simulations for Calibration and Prediction
- A Frequentist Approach to Computer Model Calibration
- Tuning parameter selectors for the smoothly clipped absolute deviation method
- A Theoretical Framework for Calibration in Computer Models: Parametrization, Estimation and Convergence Properties
- The elements of statistical learning. Data mining, inference, and prediction
This page was built for publication: Semi-parametric adjustment to computer models