Package: GPpenalty
Title: Penalized Likelihood in Gaussian Processes
Version: 1.0.1
Authors@R: 
    person("Ayumi", "Mutoh", , "amutoh@ncsu.edu", role = c("aut", "cre"))
Description: 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>), with cross-validation guided
        by decorrelated prediction error (DPE) metric. DPE metric,
        motivated by Mahalanobis distance, serves as evaluation
        criteria that accounts for predictive uncertainty in tuning
        parameter selection (Mutoh, Booth, and Stallrich, 2025,
        <doi:10.48550/arXiv.2511.18111>). Designed specifically for
        small datasets.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 3.5.0)
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, doParallel, foreach
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2026-09-25 07:16:48 UTC; root
Author: Ayumi Mutoh [aut, cre]
Maintainer: Ayumi Mutoh <amutoh@ncsu.edu>
Repository: https://cran.r-universe.dev
Date/Publication: 2025-11-26 14:20:07 UTC
RemoteUrl: https://github.com/cran/GPpenalty
RemoteRef: HEAD
RemoteSha: c116c042d6fadafccf1a319b73582426fb287508