Package: GpGp
Type: Package
Title: Fast Gaussian Process Computation Using Vecchia's Approximation
Version: 1.0.0
Date: 2025-12-17
Authors@R: c(
    person("Joseph", "Guinness", email = "joeguinness@gmail.com", role = c("aut", "cre")),
    person("Matthias", "Katzfuss", email = "katzfuss@gmail.com", role = "aut" ),
    person("Youssef", "Fahmy", email = "yf297@cornell.edu", role = "aut" ) )
Maintainer: Joseph Guinness <joeguinness@gmail.com>
Description: Functions for fitting and doing predictions with Gaussian
        process models using Vecchia's (1988) approximation. Package
        also includes functions for reordering input locations, finding
        ordered nearest neighbors (with help from 'FNN' package),
        grouping operations, and conditional simulations. Covariance
        functions for spatial and spatial-temporal data on Euclidean
        domains and spheres are provided. The original approximation is
        due to Vecchia (1988) <http://www.jstor.org/stable/2345768>,
        and the reordering and grouping methods are from Guinness
        (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting
        employs a Fisher scoring algorithm described in Guinness (2019)
        <doi:10.48550/arXiv.1905.08374>.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Imports: Rcpp (>= 0.12.13), FNN
Suggests: fields, knitr, rmarkdown, testthat, maps
LinkingTo: Rcpp, RcppArmadillo, BH
RoxygenNote: 7.3.3
LazyData: true
Repository: https://joeguinness.r-universe.dev
Date/Publication: 2025-12-17 20:31:27 UTC
RemoteUrl: https://github.com/joeguinness/gpgp
RemoteRef: HEAD
RemoteSha: 95445c66f273a957400fa6261888dd1637ee5c5f
NeedsCompilation: yes
Packaged: 2026-06-21 09:47:15 UTC; root
Author: Joseph Guinness [aut, cre],
  Matthias Katzfuss [aut],
  Youssef Fahmy [aut]