redist-package: Simulation Methods for Legislative Redistricting
In redist: Simulation Methods for Legislative Redistricting
redist-package R Documentation
Simulation Methods for Legislative Redistricting
Description
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)
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10618600.2020.1739532")}, Fifield, Imai, Kawahara, and Kenny (2020)
\Sexpr[results=rd]{tools:::Rd_expr_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.
redist documentation built on April 3, 2023, 5:46 p.m.
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| redist-package | R Documentation |
Simulation Methods for Legislative Redistricting
Description
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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10618600.2020.1739532")}, Fifield, Imai, Kawahara, and Kenny (2020) \Sexpr[results=rd]{tools:::Rd_expr_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.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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