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) <doi:10.1080/10618600.2020.1739532>, Fifield, Imai, Kawahara, and Kenny (2020) <doi: 10.1080/2330443X.2020.1791773>, and McCartan and Imai (2020) <arXiv:2008.06131>.

References

Barbu, Adrian and Song-Chun Zhu. (2005) "Generalizing Swendsen-Wang to Sampling Arbitrary Posterior Probabilities." IEEE Transactions on Pattern Analysis and Machine Intelligence.

Fifield, Benjamin, Michael Higgins, Kosuke Imai and Alexander Tarr. (2020) "Automated Redistricting Simulation Using Markov Chain Monte Carlo." Available at https://imai.fas.harvard.edu/research/files/redist.pdf.

Swendsen, Robert and Jian-Sheng Wang. (1987) "Nonuniversal Critical Dynamics in Monte Carlo Simulations." Physical Review Letters.