DESCRIPTION

Package: PrestoGP
Type: Package
Title: Penalized Regression for Spatio-Temporal Outcomes via Gaussian Processes 
Version: 0.2.0.9043
Authors@R: c(
    person(given = "Eric",
           family = "Bair",
	   role = c("aut", "cre"),
	   email = "eric.bair@sciome.com"),
    person(given = "Brian",
           family = "Kidd",
	   role = "aut"),
    person(given = "Eric",
           family = "Wimberley",
	   role = "aut"),
    person(given = "Deepak",
           family = "Mav",
	   role = "aut"),
    person(given = "Kyle",
           family = "Messier",
	   role = "aut"))
Description: Simultaneous variable seletion and estimation of LUR models with spatiotemporally correlated errors that is scalable for big data.
Depends:
    R (>= 3.5.0)
LinkingTo:
    Rcpp, RcppArmadillo, BH
Imports:
    GPvecchia,
    fields,
    dplyr,
    glmnet,
    gtools,
    RANN,
    foreach,
    rlang,
    mvtnorm,
    psych,
    MASS,
    Matrix,
    methods,
    truncnorm,
    TruncatedNormal
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr 
RoxygenNote: 7.3.2
Collate: 
    'Log_Likelihood.R'
    'PrestoGP-package.R'
    'PrestoGP_CreateU_Multivariate.R'
    'PrestoGP_Model.R'
    'PrestoGP_Vecchia.R'
    'PrestoGP_Full.R'
    'PrestoGP_Multivariate_Vecchia.R'
    'PrestoGP_Util_Functions.R'
    'RcppExports.R'
    'datadocs.R'
    'utils-tidy-eval.R'
Suggests: 
    roxygen2,
    covr,
    knitr,
    GpGp,
    geoR,
    testthat (>= 3.0.0)
Config/testthat/edition: 3
URL: https://niehs.github.io/PrestoGP/, https://github.com/NIEHS/PrestoGP