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GPpenalty: Penalized Likelihood in Gaussian Processes

Implements maximum likelihood estimation for Gaussian processes, supporting both isotropic and separable models with predictive capabilities. Includes penalized likelihood estimation following Li and Sudjianto (2005, <doi:10.1198/004017004000000671>), using score-based metrics that account for uncertainty (See Gneiting and Raftery 2007, <doi:10.1198/016214506000001437>). Includes cross validation techniques for tuning parameter selection. Designed specifically for small datasets.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: Rcpp, doParallel, foreach
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0)
Published: 2025-10-07
DOI: 10.32614/CRAN.package.GPpenalty
Author: Ayumi Mutoh [aut, cre]
Maintainer: Ayumi Mutoh <amutoh at ncsu.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
CRAN checks: GPpenalty results

Documentation:

Reference manual: GPpenalty.html , GPpenalty.pdf

Downloads:

Package source: GPpenalty_0.1.0.tar.gz
Windows binaries: r-devel: GPpenalty_0.1.0.zip, r-release: not available, r-oldrel: GPpenalty_0.1.0.zip
macOS binaries: r-release (arm64): GPpenalty_0.1.0.tgz, r-oldrel (arm64): GPpenalty_0.1.0.tgz, r-release (x86_64): GPpenalty_0.1.0.tgz, r-oldrel (x86_64): GPpenalty_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=GPpenalty 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.