Package: spmodel
Title: Spatial Statistical Modeling and Prediction
Version: 0.5.0
Authors@R: c(
    person(given = "Michael",
           family = "Dumelle",
           role = c("aut", "cre"),
           email = "Dumelle.Michael@epa.gov",
           comment = c(ORCID = "0000-0002-3393-5529")),
    person(given = "Matt",
           family = "Higham",
           role = "aut",
           email = "mhigham@stlawu.edu"),
    person(given = "Jay M.",
       family = "Ver Hoef",
       role = "aut",
       email = "jay.verhoef@noaa.gov")
    )
Description: Fit, summarize, and predict for a variety of spatial statistical models applied to point-referenced and areal (lattice) data. Parameters are estimated using various methods. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable. For additional details, see Dumelle et al. (2023) <doi:10.1371/journal.pone.0282524>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Depends: R (>= 3.5.0)
Imports: graphics, generics, Matrix, sf, stats, tibble, parallel
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), ggplot2, ranger,
        statmod
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://usepa.github.io/spmodel/
BugReports: https://github.com/USEPA/spmodel/issues
Author: Michael Dumelle [aut, cre] (<https://orcid.org/0000-0002-3393-5529>),
  Matt Higham [aut],
  Jay M. Ver Hoef [aut]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>
Built: R 4.3.1; ; 2023-10-26 17:01:05 UTC; unix
