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gaussianprocesses: Gaussian Processes from First Principles

Gaussian process regression, classification, and count models with explicit covariance kernels, exact Gaussian inference, Laplace approximations for non-Gaussian likelihoods, sparse approximations, marginal-likelihood optimization, derivatives, posterior sampling, calibration diagnostics, and time-series workflows. The implementation follows the core methodology of Rasmussen and Williams (2006) <doi:10.7551/mitpress/3206.001.0001> and emphasizes numerical stability, transparent assumptions, and reproducible statistical workflows.

Version: 1.0.0
Imports: stats
Suggests: DiceKriging, gplite, kernlab, knitr, nlme, rmarkdown, testthat (≥ 3.0.0), yaml
Published: 2026-10-21
DOI: 10.32614/CRAN.package.gaussianprocesses
Author: Diogo Ribeiro ORCID iD [aut, cre] (affiliation: Faculty of Media Arts and Design of the Technical University of Porto)
Maintainer: Diogo Ribeiro <dfr at esmad.ipp.pt>
License: MIT + file LICENSE
URL: https://gaussian-processes-r-12efed.gitlab.io/, https://gitlab.com/DiogoRibeiro7/gaussian-processes-r
NeedsCompilation: no
Language: en-US
Citation: gaussianprocesses citation info
Materials: NEWS
CRAN checks: gaussianprocesses results

Documentation:

Reference manual: gaussianprocesses.html , gaussianprocesses.pdf
Vignettes: Gaussian-Process Regression from First Principles (source, R code)
Covariance Kernels and Composition (source, R code)
Marginal Likelihood, Prediction, and Uncertainty (source, R code)
Numerical Stability in Gaussian-Process Computation (source, R code)
Multidimensional Gaussian Processes and ARD (source, R code)
Gaussian Processes for Time Series (source, R code)
Derivatives of Covariance Kernels (source, R code)

Downloads:

Package source: gaussianprocesses_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: gaussianprocesses_1.0.0.zip
macOS binaries: r-release (arm64): gaussianprocesses_1.0.0.tgz, r-oldrel (arm64): gaussianprocesses_1.0.0.tgz, r-release (x86_64): gaussianprocesses_1.0.0.tgz, r-oldrel (x86_64): gaussianprocesses_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gaussianprocesses to link to this page.

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.