diffMeshGP: Multi-Fidelity Computer Experiments Using the Tuo-Wu-Yu Model

This R function implements the nonstationary Kriging model proposed by Tuo, Wu and Yu (2014) <doi:10.1080/00401706.2013.842935> for analyzing multi-fidelity computer outputs. This function computes the maximum likelihood estimates for the model parameters as well as the predictive means and variances of the exact solution (i.e., the conceptually highest fidelity).

Version: 0.1.0
Imports: stats
Published: 2017-05-12
Author: Wenjia Wang, Rui Tuo, and C. F. Jeff Wu
Maintainer: Wenjia Wang <wenjiawang at gatech.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: diffMeshGP results


Reference manual: diffMeshGP.pdf


Package source: diffMeshGP_0.1.0.tar.gz
Windows binaries: r-devel: diffMeshGP_0.1.0.zip, r-release: diffMeshGP_0.1.0.zip, r-oldrel: diffMeshGP_0.1.0.zip
macOS binaries: r-release (arm64): diffMeshGP_0.1.0.tgz, r-oldrel (arm64): diffMeshGP_0.1.0.tgz, r-release (x86_64): diffMeshGP_0.1.0.tgz, r-oldrel (x86_64): diffMeshGP_0.1.0.tgz


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