Implements the most common Gaussian process (GP) models using Laplace and expectation propagation (EP) approximations, maximum marginal likelihood (or posterior) inference for the hyperparameters, and sparse approximations for larger datasets.
| Version: | 0.13.0 |
| Depends: | R (≥ 3.4.0) |
| Imports: | Matrix, methods,Rcpp |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | testthat,knitr,rmarkdown,ggplot2 |
| Published: | 2022-08-24 |
| DOI: | 10.32614/CRAN.package.gplite |
| Author: | Juho Piironen [cre, aut] |
| Maintainer: | Juho Piironen <juho.t.piironen at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| CRAN checks: | gplite results |
| Reference manual: | gplite.html ,gplite.pdf |
| Vignettes: | gplite Quickstart (source,R code) |
| Package source: | gplite_0.13.0.tar.gz |
| Windows binaries: | r-devel:gplite_0.13.0.zip, r-release:gplite_0.13.0.zip, r-oldrel:gplite_0.13.0.zip |
| macOS binaries: | r-release (arm64):gplite_0.13.0.tgz, r-oldrel (arm64):gplite_0.13.0.tgz, r-release (x86_64):gplite_0.13.0.tgz, r-oldrel (x86_64):gplite_0.13.0.tgz |
| Old sources: | gplite archive |
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