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shrinkGPR  

Scalable Gaussian Process Regression with Hierarchical Shrinkage Priors
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("shrinkGPR", "1.0.0")



Attach the package and use:
library("shrinkGPR")
Maintained by
Peter Knaus
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-30
Latest Update: 2025-01-30
Description:
Efficient variational inference methods for fully Bayesian Gaussian Process Regression (GPR) models with hierarchical shrinkage priors, including the triple gamma prior for effective variable selection and covariance shrinkage in high-dimensional settings. The package leverages normalizing flows to approximate complex posterior distributions. For details on implementation, see Knaus (2025) <doi:10.48550/arXiv.2501.13173>.
How to cite:
Peter Knaus (2025). shrinkGPR: Scalable Gaussian Process Regression with Hierarchical Shrinkage Priors. R package version 1.0.0, https://cran.r-project.org/web/packages/shrinkGPR. Accessed 20 Feb. 2025.
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