Package: diffMeshGP 0.1.1

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.

Authors:Wenjia Wang [aut, cre], Rui Tuo [aut], C. F. Jeff Wu [aut]

diffMeshGP_0.1.1.tar.gz
diffMeshGP_0.1.1.zip(r-4.7)diffMeshGP_0.1.1.zip(r-4.6)diffMeshGP_0.1.1.zip(r-4.5)
diffMeshGP_0.1.1.tgz(r-4.6-any)diffMeshGP_0.1.1.tgz(r-4.5-any)
diffMeshGP_0.1.1.tar.gz(r-4.7-any)diffMeshGP_0.1.1.tar.gz(r-4.6-any)
diffMeshGP_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
diffMeshGP/json (API)

# Install 'diffMeshGP' in R:

install.packages('diffMeshGP', repos = c('https://codegeasswwj.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 scripts 452 downloads 1 exports 0 dependencies

Last updated from:3dbc948c35. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	89
source / vignettes	OK	151
linux-release-x86_64	OK	103
macos-release-arm64	OK	146
macos-oldrel-arm64	OK	116
windows-devel	OK	65
windows-release	OK	59
windows-oldrel	OK	57
wasm-release	OK	82