Fast scalable Gaussian process approximations, particularly well suited to spatial (aerial, remote-sensed) and environmental data, described in more detail in Katzfuss and Guinness (2017) <doi:10.48550/arXiv.1708.06302>. Package also contains a fast implementation of the incomplete Cholesky decomposition (IC0), based on Schaefer et al. (2019) <doi:10.48550/arXiv.1706.02205> and MaxMin ordering proposed in Guinness (2018) <doi:10.48550/arXiv.1609.05372>.
| Version: |
0.1.7 |
| Imports: |
Rcpp (≥ 1.0.9), methods, stats, sparseinv, fields, Matrix (≥
1.5.1), parallel, GpGp, FNN |
| LinkingTo: |
Rcpp, RcppArmadillo, BH |
| Suggests: |
mvtnorm, knitr, rmarkdown, testthat |
| Published: |
2024-03-12 |
| DOI: |
10.32614/CRAN.package.GPvecchia |
| Author: |
Matthias Katzfuss [aut],
Marcin Jurek [aut, cre],
Daniel Zilber [aut],
Wenlong Gong [aut],
Joe Guinness [ctb],
Jingjie Zhang [ctb],
Florian Schaefer [ctb] |
| Maintainer: |
Marcin Jurek <marcinjurek1988 at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Materials: |
README, NEWS |
| CRAN checks: |
GPvecchia results |