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>.
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[aut, cre],
Jukka-Pekka Onnela