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) <arXiv:1708.06302>. Package also contains a fast implementation of the incomplete Cholesky decomposition (IC0), based on Schaefer et al. (2019) <arXiv:1706.02205> and MaxMin ordering proposed in Guinness (2018) <arXiv:1609.05372>.
Version: | 0.1.3 |
Imports: | Rcpp (≥ 0.12.16), methods, stats, sparseinv, fields, Matrix (≥ 1.2.14), parallel, GpGp, FNN |
LinkingTo: | Rcpp, RcppArmadillo, BH |
Suggests: | mvtnorm, knitr, rmarkdown, testthat |
Published: | 2020-04-22 |
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 |
Reference manual: | GPvecchia.pdf |
Vignettes: |
GPvecchia |
Package source: | GPvecchia_0.1.3.tar.gz |
Windows binaries: | r-devel: GPvecchia_0.1.3.zip, r-release: GPvecchia_0.1.3.zip, r-oldrel: GPvecchia_0.1.3.zip |
macOS binaries: | r-release: GPvecchia_0.1.3.tgz, r-oldrel: GPvecchia_0.1.3.tgz |
Old sources: | GPvecchia archive |
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