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).

Author
Giri Gopalan, Luke Bornn
Date of publication
2016-02-02 12:27:14
Maintainer
Giri Gopalan <gopalan88@gmail.com>
License
GPL-2
Version
1.2

View on CRAN

Man pages

ess
Sampling from a Bayesian model with a multivariate normal...
rcpp_matrix_ops
Matrix Operations Using Rcpp and RcppEigen
rcpp_rmvnorm
Multivariate Normal Sampling and Log-Density Evaluation

Files in this package

FastGP
FastGP/inst
FastGP/inst/doc
FastGP/inst/doc/package_article.pdf
FastGP/src
FastGP/src/rcppeigen.cpp
FastGP/src/distance.cpp
FastGP/src/invert_toeplitz.cpp
FastGP/src/RcppExports.cpp
FastGP/NAMESPACE
FastGP/demo
FastGP/demo/FastGPdemo.R
FastGP/demo/00Index
FastGP/R
FastGP/R/gpfuncs.R
FastGP/R/RcppExports.R
FastGP/R/rcpp_mvn.R
FastGP/MD5
FastGP/DESCRIPTION
FastGP/man
FastGP/man/rcpp_matrix_ops.Rd
FastGP/man/rcpp_rmvnorm.Rd
FastGP/man/ess.Rd