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GPpenalty  

Penalized Likelihood in Gaussian Processes
View on CRAN: Click here


Download and install GPpenalty package within the R console
Install from CRAN:
install.packages("GPpenalty")

Install from Github:
library("remotes")
install_github("cran/GPpenalty")

Install by package version:
library("remotes")
install_version("GPpenalty", "1.0.1")



Attach the package and use:
library("GPpenalty")
Maintained by
Ayumi Mutoh
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-10-07
Latest Update: 2025-10-07
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>), 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.
How to cite:
Ayumi Mutoh (2025). GPpenalty: Penalized Likelihood in Gaussian Processes. R package version 1.0.1, https://cran.r-project.org/web/packages/GPpenalty. Accessed 25 Jun. 2026.
Previous versions and publish date:
0.1.0 (2025-10-07 20:00), 1.0.0 (2025-11-15 23:40)
Other packages that cited GPpenalty R package
View GPpenalty citation profile
Other R packages that GPpenalty depends, imports, suggests or enhances
Complete documentation for GPpenalty
Functions, R codes and Examples using the GPpenalty R package
Full GPpenalty package functions and examples
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