Title: Fast Gaussian Process Computation Using Vecchia's Approximation
person("Joseph", "Guinness", email = "joeguinness@gmail.com", role = c("aut", "cre")),
person("Matthias", "Katzfuss", email = "katzfuss@gmail.com", role = "aut" ) )
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
<http://www.jstor.org/stable/2345768>, and the reordering and
grouping methods are from Guinness (2018)
Suggests: fields, knitr, rmarkdown, testthat

Suggests: fields, knitr, rmarkdown, testthat, maps, maptools

Description: 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.
Model fitting employs a Fisher scoring algorithm described

person("Matthias", "Katzfuss", email = "katzfuss@gmail.com", role = "aut" ),
person("Youssef", "Fahmy", email = "yf297@cornell.edu", role = "aut" ) )

Title: Graph-Constrained Estimation and Hypothesis Testing
Description: 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.

Title: Graph-Constrained Estimation and Hypothesis Tests
Description: Use the graph-constrained estimation (Grace) procedure to estimate graph-guided linear regression coefficients and use the Grace/GraceI/GraceR tests to perform graph-guided hypothesis tests on the association between the response and the predictors.

Description: Use the graph-constrained estimation (Grace) procedure (Zhao and Shojaie, 2016 <doi:10.1111/biom.12418>) to estimate graph-guided linear regression coefficients and use the Grace/GraceI/GraceR tests to perform graph-guided hypothesis tests on the association between the response and the predictors.