GpGp: Fast Gaussian Process Computation Using Vecchia's Approximation
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>.
| Version: |
0.5.1 |
| Depends: |
R (≥ 2.10) |
| Imports: |
Rcpp (≥ 0.12.13), FNN |
| LinkingTo: |
Rcpp, RcppArmadillo, BH |
| Suggests: |
fields, knitr, rmarkdown, testthat, maps |
| Published: |
2024-10-16 |
| DOI: |
10.32614/CRAN.package.GpGp |
| Author: |
Joseph Guinness [aut, cre],
Matthias Katzfuss [aut],
Youssef Fahmy [aut] |
| Maintainer: |
Joseph Guinness <joeguinness at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
yes |
| Materials: |
README NEWS |
| CRAN checks: |
GpGp results |
Documentation:
Downloads:
Reverse dependencies:
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