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GPBayes  

Tools for Gaussian Process Modeling in Uncertainty Quantification
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("GPBayes", "0.1.0-6")



Attach the package and use:
library("GPBayes")
Maintained by
Pulong Ma
[Scholar Profile | Author Map]
First Published: 2021-09-13
Latest Update: 2023-02-01
Description:
Gaussian processes ('GPs') have been widely used to model spatial data, 'spatio'-temporal data, and computer experiments in diverse areas of statistics including spatial statistics, 'spatio'-temporal statistics, uncertainty quantification, and machine learning. This package creates basic tools for fitting and prediction based on 'GPs' with spatial data, 'spatio'-temporal data, and computer experiments. Key characteristics for this GP tool include: (1) the comprehensive implementation of various covariance functions including the 'Mat
How to cite:
Pulong Ma (2021). GPBayes: Tools for Gaussian Process Modeling in Uncertainty Quantification. R package version 0.1.0-6, https://cran.r-project.org/web/packages/GPBayes. Accessed 20 Feb. 2025.
Previous versions and publish date:
0.1.0-2.1 (2021-10-08 07:20), 0.1.0-2 (2021-09-13 13:20), 0.1.0-3 (2021-12-03 06:30), 0.1.0-4 (2022-08-06 08:00), 0.1.0-5.1 (2023-02-01 12:20), 0.1.0-5 (2023-01-12 20:20)
Other packages that cited GPBayes R package
View GPBayes citation profile
Other R packages that GPBayes depends, imports, suggests or enhances
Complete documentation for GPBayes
Functions, R codes and Examples using the GPBayes R package
Some associated functions: BesselK . CH . GPBayes-package . GaSP . HypergU . cauchy . cor.to.par . deriv_kernel . distance . gp-class . gp-method . gp.fisher . gp.get.mcmc . gp.mcmc . gp.model.adequacy . gp . gp.optim . gp.predict . gp.sim . ikernel . kernel . loglik . matern . powexp . 
Some associated R codes: AllClass.R . GaSPUtils.R . RcppExports.R . startup.R . utils.R .  Full GPBayes package functions and examples
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