Jointly robust prior for Gaussian stochastic process in emulation, calibration and variable selection
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Publication:2316987
DOI10.1214/18-BA1133zbMath1421.62055arXiv1804.09329WikidataQ128820541 ScholiaQ128820541MaRDI QIDQ2316987
Publication date: 7 August 2019
Published in: Bayesian Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1804.09329
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Cites Work
- Unnamed Item
- Unnamed Item
- Scaled Gaussian Stochastic Process for Computer Model Calibration and Prediction
- Objective Bayesian analysis for a spatial model with nugget effects
- Variable selection for nonparametric Gaussian process priors: Models and computational strategies
- Efficient calibration for imperfect computer models
- Bayesian emulation of complex multi-output and dynamic computer models
- The jackknife estimate of variance
- The design and analysis of computer experiments.
- Design and analysis of computer experiments. With comments and a rejoinder by the authors
- Robust Gaussian stochastic process emulation
- Default priors for Gaussioan processes
- Parallel partial Gaussian process emulation for computer models with massive output
- Bayesian Calibration of Computer Models
- Objective Bayesian analysis of spatial data with uncertain nugget and range parameters
- A Bayesian Approach for Global Sensitivity Analysis of (Multifidelity) Computer Codes
- Computer Model Calibration Using High-Dimensional Output
- Updating Quasi-Newton Matrices with Limited Storage
- Objective Bayesian Analysis of Spatially Correlated Data
- Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- A Class of Statistics with Asymptotically Normal Distribution
- Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
- Modularization in Bayesian analysis, with emphasis on analysis of computer models