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 |