Simulation Methods for Legislative Redistricting

Enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. Tools for analysis such as computation of various summary statistics and plotting functionality are also included. The package implements methods described in Fifield, Higgins, Imai and Tarr (2020) , Fifield, Imai, Kawahara, and Kenny (2020) , and McCartan and Imai (2020) .


Reference manual

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3.0.7 by Christopher T. Kenny, a month ago

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Authors: Christopher T. Kenny [aut, cre] , Cory McCartan [aut] , Ben Fifield [aut] , Kosuke Imai [aut] , Jun Kawahara [ctb] , Alexander Tarr [ctb] , Michael Higgins [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, rlang, vctrs, tidyselect, stringr, dplyr, sf, doParallel, foreach, servr, sys, coda, ggplot2, patchwork, readr

Suggests igraph, s2, lwgeom, withr, loo, Rmpi, knitr, rmarkdown, rmapshaper, scales, units, spdep, RSpectra, testthat

Linking to Rcpp, RcppArmadillo

System requirements: OpenMPI, gmp, libxml2, python

Suggested by geomander.

See at CRAN