Calibration, Validation, and Prediction in Random Simulation Models
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Publication:5270741
DOI10.1145/2699713zbMath1371.65016OpenAlexW1981417332MaRDI QIDQ5270741
Publication date: 30 June 2017
Published in: ACM Transactions on Modeling and Computer Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1145/2699713
predictionnumerical exampleGaussian processBayesian approachsequential experimental designcomputer model calibrationstochastic computer simulation
Inference from stochastic processes and prediction (62M20) Gaussian processes (60G15) Design of statistical experiments (62K99) Bayesian inference (62F15) Probabilistic models, generic numerical methods in probability and statistics (65C20) Monte Carlo methods (65C05)
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Cites Work
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- The design and analysis of computer experiments.
- Multivariate versus univariate Kriging metamodels for multi-response simulation models
- Stochastic Kriging for Simulation Metamodeling
- On a Measure of the Information Provided by an Experiment
- The effects of common random numbers on stochastic kriging metamodels
- Bayesian Kriging Analysis and Design for Stochastic Simulations
- Goodness-of-fit tests based on Kullback-Leibler discrimination information
- On prediction intervals based on predictive likelihood or bootstrap methods
- Statistics for Spatial Data
- Bayesian Emulation and Calibration of a Stochastic Computer Model of Mitochondrial DNA Deletions in Substantia Nigra Neurons