Package: FastGP
Type: Package
Title: Efficiently Using Gaussian Processes with Rcpp and RcppEigen
Version: 1.5
Date: 2026-10-17
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 inverse and determinant of a symmetric and positive-definite 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
Suggests: microbenchmark
LinkingTo: Rcpp, RcppEigen
Repository: CRAN
NeedsCompilation: yes
RoxygenNote: 7.3.1
Author: Giri Gopalan [aut, cre],
  Luke Bornn [aut]
Packaged: 2026-10-16 18:16:28 UTC; ggopalan
Date/Publication: 2026-10-17 19:00:02 UTC
Built: R 4.6.1; x86_64-apple-darwin20; 2026-10-17 20:28:18 UTC; unix
Archs: FastGP.so.dSYM
