Package: disaggregation
Type: Package
Title: Disaggregation Modelling
Version: 0.1.3
Authors@R: c(
    person("Anita", "Nandi", email = "anita.k.nandi@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5087-2494")),
    person("Tim", "Lucas", email =  "timcdlucas@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-4694-8107")),
    person("Rohan", "Arambepola", email = "rarambepola@gmail.com", role = "aut"),
    person("Andre", "Python", email = "python.andre@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-8094-7226"))
    )
Description: Fits disaggregation regression models using 'TMB' ('Template Model
    Builder'). When the response data are aggregated to polygon level but
    the predictor variables are at a higher resolution, these models can be
    useful. Regression models with spatial random fields. A useful reference for disaggregation modelling is 
    Lucas et al. (2019) <doi:10.1101/548719>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: maptools, raster, foreach, sp, parallel, doParallel, rgeos,
        splancs, rgdal, Matrix, stats, TMB, dplyr, ggplot2, cowplot,
        sparseMVN, utils
Additional_repositories: https://inla.r-inla-download.org/R/stable
Suggests: testthat, INLA, knitr, rmarkdown, SpatialEpi
LinkingTo: TMB, RcppEigen
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-02-18 16:44:27 UTC; anitan
Author: Anita Nandi [aut, cre] (<https://orcid.org/0000-0002-5087-2494>),
  Tim Lucas [aut] (<https://orcid.org/0000-0003-4694-8107>),
  Rohan Arambepola [aut],
  Andre Python [aut] (<https://orcid.org/0000-0001-8094-7226>)
Maintainer: Anita Nandi <anita.k.nandi@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-19 12:50:02 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 13:46:43 UTC; windows
Archs: i386, x64
