``redist: Markov Chain Monte Carlo Methods for Redistricting Simulation.''



This open-source software package 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 (2015) ``A New Automated Redistricting Simulator Using Markov Chain Monte Carlo.''

  Source Code

The source code and the documentation are available for download from the Comprehensive R Archive Network and the GitHub repository.

© Kosuke Imai
Last modified: Sun May 24 19:43:50 EDT 2015