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bhetGP
View on CRAN: Click
here
Download and install bhetGP package within the R console
Install from CRAN:
install.packages("bhetGP")
Install from Github:
library("remotes")
install_github("cran/bhetGP") Install by package version:
library("remotes")
install_version("bhetGP", "1.0.1") Attach the package and use:
library("bhetGP")
Maintained by
Parul V. Patil
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-07-14
Latest Update: 2025-07-18
Description:
Performs Bayesian posterior inference for heteroskedastic Gaussian processes. Models are trained through MCMC including elliptical slice sampling (ESS) of latent noise processes and Metropolis-Hastings sampling of kernel hyperparameters. Replicates are handled efficientyly through a Woodbury formulation of the joint likelihood for the mean and noise process (Binois, M., Gramacy, R., Ludkovski, M. (2018) <doi:10.1080/10618600.2018.1458625>) For large data, Vecchia-approximation for faster computation is leveraged (Sauer, A., Cooper, A., and Gramacy, R., (2023), <doi:10.1080/10618600.2022.2129662>). Incorporates 'OpenMP' and SNOW parallelization and utilizes 'C'/'C++' under the hood.
How to cite:
Parul V. Patil (2025). bhetGP: Bayesian Heteroskedastic Gaussian Processes. R package version 1.0.1, https://cran.r-project.org/web/packages/bhetGP. Accessed 14 Mar. 2026.
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