Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model Evaluations
From MaRDI portal
Publication:5075228
DOI10.1137/20M1318560zbMath1485.62169OpenAlexW4220926580MaRDI QIDQ5075228
No author found.
Publication date: 10 May 2022
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/20m1318560
Gaussian processes (60G15) Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Exploratory designs for computational experiments
- Multilevel modeling using spatial processes: application to the Singapore housing market
- Bayesian emulation of complex multi-output and dynamic computer models
- The design and analysis of computer experiments.
- Bayesian experimental design: A review
- Composite Gaussian process models for emulating expensive functions
- Galaxy formation: a Bayesian uncertainty analysis
- Bayesian Calibration of Computer Models
- A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
- Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
- Gaussian process emulation of dynamic computer codes
- Bayes Linear Statistics
- Computer Model Calibration Using High-Dimensional Output
- The linear Bayes regression estimator under weak prior assumptions
- Bayesian analysis of regression problems
- Spatial Modeling With Spatially Varying Coefficient Processes
- Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach
- Diagnostics-Driven Nonstationary Emulators Using Kernel Mixtures
- Analyzing Nonstationary Spatial Data Using Piecewise Gaussian Processes
This page was built for publication: Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model Evaluations
