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
NeedsCompilation: yes
Packaged: 2025-12-17 20:33:01 UTC; joe
Author: Joseph Guinness [aut, cre],
  Matthias Katzfuss [aut],
  Youssef Fahmy [aut]
Repository: CRAN
Date/Publication: 2025-12-18 06:11:10 UTC
Built: R 4.5.2; x86_64-w64-mingw32; 2025-12-27 02:08:20 UTC; windows
Archs: x64
