redist

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 the SMC algorithm of McCartan and Imai (2023) doi:10.1214/23-AOAS1763, the enumeration algorithm of Fifield, Imai, Kawahara, and Kenny (2020) doi:10.1080/2330443X.2020.1791773, the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) doi:10.1080/10618600.2020.1739532, the Merge-split/Recombination algorithms of Carter et al. (2019) doi:10.48550/arXiv.1911.01503 and DeFord et al. (2021) doi:10.1162/99608f92.eb30390f, and the Short-burst optimization algorithm of Cannon et al. (2020) doi:10.48550/arXiv.2011.02288.

Last 30 days

This package has been downloaded 334 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 4,731 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Feb 20, 2025 with 71 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.