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Implements full Bayesian analysis for calibrating mathematical models with new methodology for modeling the discrepancy function. It allows for emulation, calibration and prediction using complex mathematical model outputs and experimental data. See the reference: Mengyang Gu and Long Wang, 2018, Journal of Uncertainty Quantification; Mengyang Gu, Fangzheng Xie and Long Wang, 2022, Journal of Uncertainty Quantification; Mengyang Gu, Kyle Anderson and Erika McPhillips, 2023, Technometrics.
Version: | 0.5.5 |
Depends: | methods |
Imports: | Rcpp (≥ 0.12.3), RobustGaSP (≥ 0.6.4), nloptr (≥ 1.0.4) |
LinkingTo: | Rcpp, RcppEigen |
Published: | 2024-05-30 |
DOI: | 10.32614/CRAN.package.RobustCalibration |
Author: | Mengyang Gu [aut, cre] |
Maintainer: | Mengyang Gu <mengyang at pstat.ucsb.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Materials: | ChangeLog |
CRAN checks: | RobustCalibration results |
Reference manual: | RobustCalibration.pdf |
Package source: | RobustCalibration_0.5.5.tar.gz |
Windows binaries: | r-devel: RobustCalibration_0.5.5.zip, r-release: RobustCalibration_0.5.5.zip, r-oldrel: RobustCalibration_0.5.5.zip |
macOS binaries: | r-release (arm64): RobustCalibration_0.5.5.tgz, r-oldrel (arm64): RobustCalibration_0.5.5.tgz, r-release (x86_64): RobustCalibration_0.5.5.tgz, r-oldrel (x86_64): RobustCalibration_0.5.5.tgz |
Old sources: | RobustCalibration archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.