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bigGP  

Distributed Gaussian Process Calculations
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("bigGP", "0.1.8")



Attach the package and use:
library("bigGP")
Maintained by
Christopher Paciorek
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-06-04
Latest Update: 2023-04-25
Description:
Distributes Gaussian process calculations across nodes in a distributed memory setting, using Rmpi. The bigGP class provides high-level methods for maximum likelihood with normal data, prediction, calculation of uncertainty (i.e., posterior covariance calculations), and simulation of realizations. In addition, bigGP provides an API for basic matrix calculations with distributed covariance matrices, including Cholesky decomposition, back/forwardsolve, crossproduct, and matrix multiplication.
How to cite:
Christopher Paciorek (2013). bigGP: Distributed Gaussian Process Calculations. R package version 0.1.8, https://cran.r-project.org/web/packages/bigGP. Accessed 06 Jan. 2025.
Previous versions and publish date:
0.1-2 (2013-06-04 16:01), 0.1-3 (2014-05-24 19:28), 0.1-4 (2014-12-06 07:21), 0.1-5 (2015-01-21 07:22), 0.1-6 (2015-07-08 13:49), 0.1-7 (2021-10-31 00:30)
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Complete documentation for bigGP
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