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

Linking:

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