katzfuss-group/GPvecchia: Scalable Gaussian-Process Approximations
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>.
Getting started
Browse package contents
Package details |
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| 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@gmail.com> |
| License | GPL (>=2) |
| Version | 0.1.5 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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