Package: sim2Dpredictr
Title: Simulate Outcomes Using Spatially Dependent Design Matrices
Version: 0.1.1
Authors@R: person("Justin", "Leach", email = "jleach@uab.edu", role = c("aut", "cre", "cph"))
Description: Provides tools for simulating spatially dependent
        predictors (continuous or binary), which are used to generate
        scalar outcomes in a (generalized) linear model framework.
        Continuous predictors are generated using traditional
        multivariate normal distributions or Gauss Markov random fields
        with several correlation function approaches (e.g., see Rue
        (2001) <doi:10.1111/1467-9868.00288> and Furrer and Sain (2010)
        <doi:10.18637/jss.v036.i10>), while binary predictors are
        generated using a Boolean model (see Cressie and Wikle (2011,
        ISBN: 978-0-471-69274-4)). Parameter vectors exhibiting spatial
        clustering can also be easily specified by the user.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
Imports: MASS, Rdpack, spam (>= 2.2-0), tibble, dplyr, matrixcalc
RdMacros: Rdpack
RoxygenNote: 7.2.3
Suggests: knitr, rmarkdown, testthat, V8
URL: https://github.com/jmleach-bst/sim2Dpredictr
BugReports: https://github.com/jmleach-bst/sim2Dpredictr
Repository: https://jmleach-bst.r-universe.dev
Date/Publication: 2024-02-29 18:39:07 UTC
RemoteUrl: https://github.com/jmleach-bst/sim2dpredictr
RemoteRef: HEAD
RemoteSha: 339a4aef8ec18c2e3e398e05c9ee4c6c410b2af1
NeedsCompilation: no
Packaged: 2026-10-01 10:44:20 UTC; root
Author: Justin Leach [aut, cre, cph]
Maintainer: Justin Leach <jleach@uab.edu>