Fast Gaussian Process Computation Using Vecchia's Approximation
c(
person("Joseph", "Guinness", email = "joeguinness@gmail.com", role = c("aut", "cre")),
person("Matthias", "Katzfuss", email = "katzfuss@gmail.com", role = "aut" ) )
Functions for reordering
input locations, finding ordered nearest neighbors
(with help from 'FNN' package), grouping operations,
approximate likelihood evaluations, profile likelihoods,
Gaussian process predictions, 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>.
Joseph Guinness [aut, cre],
Matthias Katzfuss [aut]

fields, knitr, rmarkdown, testthat, maps, maptools

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>.

c(
person("Joseph", "Guinness", email = "joeguinness@gmail.com", role = c("aut", "cre")),
person("Matthias", "Katzfuss", email = "katzfuss@gmail.com", role = "aut" ),
person("Youssef", "Fahmy", email = "yf297@cornell.edu", role = "aut" ) )
Joseph Guinness [aut, cre],
Matthias Katzfuss [aut],
Youssef Fahmy [aut]

Graph-Constrained Estimation and Hypothesis Testing
Use the graph-constrained estimation (Grace) procedure to estimate graph-guided linear regression coefficients and use the Grace and GraceR tests to perform graph-guided hypothesis test on the association between the response and the predictor.