Scalable Gaussian-Process Approximations R package GPvecchia version 0.1.8 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>. Software Imports: Rcpp (>= 1.1.1), methods, stats, sparseinv, fields, Matrix(>= 1.5.1), parallel, GpGp, FNN LinkingTo: Rcpp, RcppArmadillo, BH Suggests: mvtnorm, knitr, rmarkdown, testthat Marcin Jurek <marcinjurek1988@gmail.com> Comprehensive R Archive Network (CRAN) Matthias Katzfuss [aut], Marcin Jurek [aut, cre], Daniel Zilber [aut], Wenlong Gong [aut], Joe Guinness [ctb], Jingjie Zhang [ctb], Florian Schaefer [ctb] GPL (>= 2) 2026-01-31 application/tgz https://CRAN.R-project.org/package=GPvecchia doi:10.32614/CRAN.package.GPvecchia