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RobustCalibration: Robust Calibration of Imperfect Mathematical Models

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

Documentation:

Reference manual: RobustCalibration.pdf

Downloads:

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

Linking:

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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.