Package: rkriging 1.1.0

Difan Song

rkriging: Kriging Modeling

An 'Eigen'-based computationally efficient 'C++' implementation for fitting various kriging models to data. This research is supported by U.S. National Science Foundation grant DMS-2310637.

Authors:Chaofan Huang [aut], Difan Song [aut, cre], V. Roshan Joseph [aut]

rkriging_1.1.0.tar.gz
rkriging_1.1.0.zip(r-4.7-x86_64)rkriging_1.1.0.zip(r-4.7-arm64)rkriging_1.1.0.zip(r-4.6-x86_64)rkriging_1.1.0.zip(r-4.6-arm64)
rkriging_1.1.0.tar.gz(r-4.7-arm64)rkriging_1.1.0.tar.gz(r-4.7-x86_64)rkriging_1.1.0.tar.gz(r-4.6-arm64)rkriging_1.1.0.tar.gz(r-4.6-x86_64)
rkriging_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rkriging/json (API)

# Install 'rkriging' in R:
install.packages('rkriging', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

cpp

2.02 score 2 stars 52 scripts 257 downloads 33 exports 4 dependencies

Last updated from:7e0cc44352. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK208
linux-devel-x86_64OK241
source / vignettesOK251
linux-release-arm64OK201
linux-release-x86_64OK232
windows-devel-arm64OK332
windows-devel-x86_64OK283
windows-release-arm64OK303
windows-release-x86_64OK283
wasm-releaseOK151

Exports:Add.Next.DesignALM.SequentialEI.SequentialEvaluate.KernelFit.KrigingGaussian.KernelGeneralized.Rational.KrigingGet.Best.DesignGet.DataGet.KernelGet.Kriging.ParametersGet.Next.DesignGet.SequentialIM.KernelLimit.KrigingMatern.KernelMatern12.KernelMatern32.KernelMatern52.KernelMultiplicativeIM.KernelMultiplicativeMatern.KernelMultiplicativeRQ.KernelMultiplicativeUDF.KernelOrdinary.KrigingPI.SequentialPredict.KrigingPredict.SequentialRational.KrigingRQ.KernelUCB.SequentialUDF.KernelUDF.SequentialUniversal.Kriging

Dependencies:BHnloptrRcppRcppEigen