README.md

In GpGp: Fast Gaussian Process Computation Using Vecchia's Approximation

GpGp

GpGp is an R package for fast approximate Gaussian process computation. The package includes implementations of the Vecchia's (1988) original approximation, as well as several updates to it, including the reordered and grouped versions of the approximation outlined in Guinness (2018).

Installing

The package can be installed from CRAN with the usual R command

install.packages("GpGp")

or directly from Github for the latest version

devtools::install_github("joeguinness/GpGp")

We always recommend using multithreaded linear algebra libraries in R, but for this package in particular, using multithreaded libraries can have a big impact on performance. On a Mac, there is a very simple way to link to the Apple Accelerate Framework. On PC and Linux, it's more complicated, but you can use Microsoft R Open instead, which comes automatically with multithreaded libraries.

Basic Use

The main function for fitting models is called 'fit_model', and the main function for doing predictions is called 'predictions'.

See this youtube video for a tutorial: https://www.youtube.com/watch?v=phyB4n0CDWg&t=4s

GpGp documentation built on June 10, 2021, 1:07 a.m.