Package: BayesGPfit 1.1.0

BayesGPfit: Fast Bayesian Gaussian Process Regression Fitting

Bayesian inferences on nonparametric regression via Gaussian Processes with a modified exponential square kernel using a basis expansion approach.

Authors:Jian Kang [aut, cre], John Burkardt [ctb]

BayesGPfit_1.1.0.tar.gz
BayesGPfit_1.1.0.zip(r-4.7-x86_64)BayesGPfit_1.1.0.zip(r-4.7-arm64)BayesGPfit_1.1.0.zip(r-4.6-x86_64)BayesGPfit_1.1.0.zip(r-4.6-arm64)BayesGPfit_1.1.0.zip(r-4.5-x86_64)
BayesGPfit_1.1.0.tgz(r-4.6-x86_64)BayesGPfit_1.1.0.tgz(r-4.6-arm64)BayesGPfit_1.1.0.tgz(r-4.5-x86_64)BayesGPfit_1.1.0.tgz(r-4.5-arm64)
BayesGPfit_1.1.0.tar.gz(r-4.7-arm64)BayesGPfit_1.1.0.tar.gz(r-4.7-x86_64)BayesGPfit_1.1.0.tar.gz(r-4.6-arm64)BayesGPfit_1.1.0.tar.gz(r-4.6-x86_64)
BayesGPfit_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BayesGPfit/json (API)

# Install 'BayesGPfit' in R:
install.packages('BayesGPfit', repos = c('https://kangjian2016.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kangjian2016/bayesgpfit/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

4.65 score 4 stars 1 packages 74 scripts 382 downloads 14 exports 1 dependencies

Last updated from:8cb69a5b8c. Checks:13 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR74
linux-devel-x86_64ERROR92
source / vignettesOK191
linux-release-arm64ERROR73
linux-release-x86_64ERROR94
macos-release-arm64ERROR96
macos-release-x86_64ERROR184
macos-oldrel-arm64ERROR108
macos-oldrel-x86_64ERROR237
windows-devel-arm64ERROR302
windows-devel-x86_64ERROR114
windows-release-arm64ERROR282
windows-release-x86_64ERROR89
windows-oldrel-x86_64ERROR82
wasm-releaseOK72

Exports:GP.Bayes.fitGP.create.colsGP.eigen.funcs.fastGP.eigen.funcs.fast.orthGP.eigen.valueGP.fast.Bayes.fitGP.generate.gridsGP.plot.curveGP.plot.curvesGP.predictGP.simulate.curve.fastGP.simulate.curves.fastGP.std.gridsGP.summary

Dependencies:lattice