gptoolsStan: Gaussian Processes on Graphs and Lattices in 'Stan'

Gaussian processes are flexible distributions to model functional data. Whilst theoretically appealing, they are computationally cumbersome except for small datasets. This package implements two methods for scaling Gaussian process inference in 'Stan'. First, a sparse approximation of the likelihood that is generally applicable and, second, an exact method for regularly spaced data modeled by stationary kernels using fast Fourier methods. Utility functions are provided to compile and fit 'Stan' models using the 'cmdstanr' interface. References: Hoffmann and Onnela (2022) <doi:10.48550/arXiv.2301.08836>.

Version: 0.1.0
Suggests: knitr, rmarkdown, cmdstanr
Published: 2023-12-19
Author: Till Hoffmann ORCID iD [aut, cre], Jukka-Pekka Onnela ORCID iD [ctb]
Maintainer: Till Hoffmann <thoffmann at hsph.harvard.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Additional_repositories: https://mc-stan.org/r-packages/
Language: en-US
Materials: README NEWS
CRAN checks: gptoolsStan results

Documentation:

Reference manual: gptoolsStan.pdf
Vignettes: Getting Started with gptools in R

Downloads:

Package source: gptoolsStan_0.1.0.tar.gz
Windows binaries: r-devel: gptoolsStan_0.1.0.zip, r-release: gptoolsStan_0.1.0.zip, r-oldrel: gptoolsStan_0.1.0.zip
macOS binaries: r-release (arm64): gptoolsStan_0.1.0.tgz, r-oldrel (arm64): gptoolsStan_0.1.0.tgz, r-release (x86_64): gptoolsStan_0.1.0.tgz

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