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FastGP: Efficiently Using Gaussian Processes with Rcpp and RcppEigen

Contains Rcpp and RcppEigen implementations of matrix operations useful for Gaussian process models, such as the inversion of a symmetric Toeplitz matrix, sampling from multivariate normal distributions, evaluation of the log-density of a multivariate normal vector, and Bayesian inference for latent variable Gaussian process models with elliptical slice sampling (Murray, Adams, and MacKay 2010).

Version:1.2
Imports:Rcpp,MASS,mvtnorm,rbenchmark, stats
LinkingTo:Rcpp,RcppEigen
Published:2016-02-02
DOI:10.32614/CRAN.package.FastGP
Author:Giri Gopalan, Luke Bornn
Maintainer:Giri Gopalan <gopalan88 at gmail.com>
License:GPL-2
NeedsCompilation:yes
CRAN checks:FastGP results

Documentation:

Reference manual:FastGP.html ,FastGP.pdf

Downloads:

Package source: FastGP_1.2.tar.gz
Windows binaries: r-devel:FastGP_1.2.zip, r-release:FastGP_1.2.zip, r-oldrel:FastGP_1.2.zip
macOS binaries: r-release (arm64):FastGP_1.2.tgz, r-oldrel (arm64):FastGP_1.2.tgz, r-release (x86_64):FastGP_1.2.tgz, r-oldrel (x86_64):FastGP_1.2.tgz
Old sources: FastGP archive

Reverse dependencies:

Reverse imports:BayesMFSurv,countSTAR,GeoModels,TAG

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=FastGPto link to this page.


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