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BayesGPfit
View on CRAN: Click
here
Download and install BayesGPfit package within the R console
Install from CRAN:
install.packages("BayesGPfit")
Install from Github:
library("remotes")
install_github("cran/BayesGPfit") Install by package version:
library("remotes")
install_version("BayesGPfit", "1.1.0") Attach the package and use:
library("BayesGPfit")
Maintained by
Jian Kang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-20
Latest Update: 2022-08-06
Description:
Bayesian inferences on nonparametric regression via Gaussian Processes with a modified exponential square kernel using a basis expansion approach.
How to cite:
Jian Kang (2020). BayesGPfit: Fast Bayesian Gaussian Process Regression Fitting. R package version 1.1.0, https://cran.r-project.org/web/packages/BayesGPfit. Accessed 22 Sep. 2026.
Previous versions and publish date:
0.1.0 (2020-02-20 17:10), (2026-07-09 07:58)
Other packages that cited BayesGPfit R package
View BayesGPfit citation profile
Other R packages that BayesGPfit depends,
imports, suggests or enhances
Complete documentation for BayesGPfit
Functions, R codes and Examples using
the BayesGPfit R package
Some associated functions: GP.Bayes.fit . GP.create.cols . GP.eigen.funcs.fast . GP.eigen.funcs.fast.orth . GP.eigen.value . GP.fast.Bayes.fit . GP.generate.grids . GP.plot.curve . GP.plot.curves . GP.predict . GP.simulate.curve.fast . GP.simulate.curves.fast . GP.std.grids . GP.summary .
Some associated R codes: fastGPfit.R . Full BayesGPfit package functions and examples
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