Package: FastGP
Type: Package
Title: Efficiently Using Gaussian Processes with Rcpp and RcppEigen
Version: 1.3
Date: 2026-04-28
Authors@R: c(
    person(given = "Giri",
           family = "Gopalan",
           role = c("aut", "cre"),
           email = "gopalan88@gmail.com"),
    person(given = "Luke",
           family = "Bornn",
           role = "aut")
  )
Maintainer: Giri Gopalan <gopalan88@gmail.com>
Description: 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).
License: GPL-2
Imports: Rcpp, MASS, mvtnorm, stats
LinkingTo: Rcpp, RcppEigen
Repository: CRAN
NeedsCompilation: yes
RoxygenNote: 7.3.1
Packaged: 2026-04-29 04:35:42 UTC; ggopalan
Author: Giri Gopalan [aut, cre],
  Luke Bornn [aut]
Date/Publication: 2026-04-29 06:40:31 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-05-01 20:14:47 UTC; unix
Archs: FastGP.so.dSYM
