GaSP (Q159758)
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Train and Apply a Gaussian Stochastic Process Model
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | GaSP |
Train and Apply a Gaussian Stochastic Process Model |
Statements
8 December 2023
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Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, <doi:10.1214/ss/1177012413>. Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", <doi:10.1007/0-387-28014-6_14>.
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