GpGp: Fast Gaussian Process Computation Using Vecchia's Approximation

Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) <http://www.jstor.org/stable/2345768>, and the reordering and grouping methods are from Guinness (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) <arXiv:1905.08374>.

Getting started

Package details

AuthorJoseph Guinness [aut, cre], Matthias Katzfuss [aut]
MaintainerJoseph Guinness <[email protected]>
LicenseMIT + file LICENSE
Version0.2.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("GpGp")

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GpGp documentation built on July 9, 2019, 5:02 p.m.