Package: redist
Version: 1.3-3
Date: 2018-12-15
Title: Markov Chain Monte Carlo Methods for Redistricting Simulation
Author: Ben Fifield <bfifield@princeton.edu>, Alexander Tarr
    <atarr@princeton.edu>, Michael Higgins <mikehiggins@k-state.edu>, and Kosuke
    Imai <imai@harvard.edu>
Maintainer: Ben Fifield <bfifield@princeton.edu>
Description: Enables researchers to sample redistricting plans from a pre-
    specified target distribution using a Markov Chain Monte Carlo algorithm.
    The package allows for the implementation of various constraints in the
    redistricting process such as geographic compactness and population parity
    requirements. The algorithm also can be used in combination with efficient
    simulation methods such as simulated and parallel tempering algorithms. Tools
    for analysis such as inverse probability reweighting and plotting functionality
    are included. The package implements methods described in Fifield, Higgins, Imai
    and Tarr (2016) ``A New Automated Redistricting Simulator Using Markov Chain
    Monte Carlo,'' working paper available at
    <https://imai.fas.harvard.edu/research/files/redist.pdf>.
Depends: R (>= 3.1.0)
Imports: Rcpp (>= 0.11.0), spdep, sp, coda, parallel, doParallel,
        foreach
Suggests: testthat, Rmpi
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 2)
SystemRequirements: gmp, libxml2
Packaged: 2018-12-15 20:17:56 UTC; benfifield
NeedsCompilation: yes
BugReports: https://github.com/kosukeimai/redist/issues
RoxygenNote: 6.0.1
Repository: CRAN
Date/Publication: 2018-12-15 20:40:03 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 07:35:16 UTC; windows
Archs: i386, x64
