Optimal Legislative County Clustering in North Carolina

Author:

Carter Daniel1,Hunter Zach1,Teague Dan1,Herschlag Gregory2ORCID,Mattingly Jonathan23

Affiliation:

1. North Carolina School of Science and Mathematics, Durham, NC;

2. Department of Mathematics, Duke University, Durham, NC;

3. Department of Statistical Science, Duke University, Durham, NC

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Public Administration,Statistics and Probability

Reference11 articles.

1. Bangia, S., Graves, C. V., Herschlag, G., Kang, H. S., Luo, J., Mattingly, J. C., and Ravier, R. (2017), “Redistricting: Drawing the Line,” arXiv no. 1704.03360.

2. Carter, D., Herschlag, G., Hunter, Z., and Mattingly, J. (2019), “A Merge-Split Proposal for Reversible Monte Carlo Markov Chain Sampling of Redistricting Plans,” arXiv no. 1911.01503.

3. DeFord, D., Duchin, M., and Solomon, J. (2019), “Recombination: A Family of Markov Chains for Redistricting,” arXiv no. 1911.05725.

4. Fifield, B., Higgins, M., Imai, K., and Tarr, A. (2015), “A New Automated Redistricting Simulator Using Markov Chain Monte Carlo,” Working Paper, Princeton University, Princeton, NJ.

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