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
NeedsCompilation: no
Packaged: 2023-04-03 12:36:37 UTC; cotto
Author: Justin Leach [aut, cre, cph]
Maintainer: Justin Leach <jleach@uab.edu>
Repository: CRAN
Date/Publication: 2023-04-03 13:00:02 UTC
Built: R 4.6.0; ; 2026-04-26 15:11:01 UTC; unix
