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: GPpenalty_0.1.0.zip, 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:

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