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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.pdf |
| Vignettes: |
gplite Quickstart |
| 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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.