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>
License: GPL-2
NeedsCompilation: yes
CRAN checks: FastGP results


Reference manual: FastGP.pdf


Package source: FastGP_1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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, fdaPOIFD, GeoModels, TAG


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