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 .

Documentation

Manual: redist.pdf
Vignette: None available.

Maintainer: Ben Fifield <bfifield at princeton.edu>

Author(s): Ben Fifield <bfifield at princeton.edu>, Alexander Tarr <atarr at princeton.edu>, Michael Higgins <mikehiggins at k-state.edu>, and Kosuke Imai <kimai at princeton.edu>

Install package and any missing dependencies by running this line in your R console:

install.packages("redist")

Depends R (>= 3.1.0)
Imports Rcpp(>=0.11.0), spdep, sp, coda, parallel, doParallel, foreach
Suggests testthat, Rmpi
Enhances
Linking to Rcpp, RcppArmadillo
Reverse
depends
Reverse
imports
Reverse
suggests
Reverse
enhances
Reverse
linking to

Package redist
Materials
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Version 1.3-1
Published 2017-03-15
License GPL (>= 2)
BugReports
SystemRequirements gmp, libxml2
NeedsCompilation yes
Citation
CRAN checks redist check results
Package source redist_1.3-1.tar.gz