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diffMeshGP  

Multi-Fidelity Computer Experiments Using the Tuo-Wu-Yu Model
View on CRAN: Click here


Download and install diffMeshGP package within the R console
Install from CRAN:
install.packages("diffMeshGP")

Install from Github:
library("remotes")
install_github("cran/diffMeshGP")

Install by package version:
library("remotes")
install_version("diffMeshGP", "0.1.1")



Attach the package and use:
library("diffMeshGP")
Maintained by
Wenjia Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-12
Latest Update:
Description:
This R function implements the nonstationary Kriging model proposed by Tuo, Wu and Yu (2014) 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).
How to cite:
Wenjia Wang (2017). diffMeshGP: Multi-Fidelity Computer Experiments Using the Tuo-Wu-Yu Model. R package version 0.1.1, https://cran.r-project.org/web/packages/diffMeshGP. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.1.0 (2017-05-12 08:12)
Other packages that cited diffMeshGP R package
View diffMeshGP citation profile
Other R packages that diffMeshGP depends, imports, suggests or enhances
Complete documentation for diffMeshGP
Functions, R codes and Examples using the diffMeshGP R package
Some associated functions: GPdiffMesh . 
Some associated R codes: GPdiffMesh.R .  Full diffMeshGP package functions and examples
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