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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 |
| Reference manual: | GPpenalty.html , GPpenalty.pdf |
| 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 |
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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.