# 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

See the vignettes directory for examples using the package. The file vignette_likelihood.R shows how to use the low-level functions to reorder, find neighbors, group, and calculate likelihoods. The file vignette_windspeed.R shows an analysis of spatial-temporal windspeed data using higher-level functions (i.e. more automation).