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Journal of Computational and Graphical Statistics Volume 29, 2020 - Issue 4
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Monte Carlo and Approximation Methods

Automated Redistricting Simulation Using Markov Chain Monte Carlo

Benjamin FifieldInstitute for Quantitative Social Science, Harvard University, Cambridge, MA;
,
, Michael HigginsDepartment of Statistics, Kansas State University, Manhattan, KS;
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Kosuke ImaiInstitute for Quantitative Social Science, Harvard University, Cambridge, MA; ;Department of Government, Harvard University, Cambridge, MA; ;Department of Statistics, Harvard University, Cambridge, MA; Correspondence[email protected]
ORCID Iconhttp://orcid.org/0000-0002-2748-1022
ORCID Icon &
Alexander TarrDepartment of Electrical Engineering, Princeton University, Princeton, NJ
Pages 715-728 | Received 14 Oct 2018, Accepted 25 Feb 2020, Published online: 07 May 2020

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Annika King, Jacob Murri, Jake Callahan, Adrienne Russell & Tyler J. Jarvis. (2022) Mathematical Analysis of Redistricting in Utah. Statistics and Public Policy 9:1, pages 136-148.
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Benjamin Fifield, Kosuke Imai, Jun Kawahara & Christopher T. Kenny. (2020) The Essential Role of Empirical Validation in Legislative Redistricting Simulation. Statistics and Public Policy 7:1, pages 52-68.
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Daryl DeFord, Moon Duchin & Justin Solomon. (2020) A Computational Approach to Measuring Vote Elasticity and Competitiveness. Statistics and Public Policy 7:1, pages 69-86.
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Cory McCartan & Kosuke Imai. (2023) Sequential Monte Carlo for sampling balanced and compact redistricting plans. The Annals of Applied Statistics 17:4.
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Kiera W. Dobbs, Rahul Swamy, Douglas M. King, Ian G. Ludden & Sheldon H. Jacobson. (2023) An Optimization Case Study in Analyzing Missouri Redistricting. INFORMS Journal on Applied Analytics.
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Kiera W. Dobbs, Douglas M. King & Sheldon H. Jacobson. (2023) Redistricting optimization with recombination: A local search case study. Computers & Operations Research, pages 106369.
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Adeline Lo, Devin Judge-Lord, Kyler Hudson & Kenneth R. Mayer. (2023) Mapping Literature with Networks: An Application to Redistricting. Political Analysis, pages 1-10.
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Marcello Schiavina, Michele Melchiorri & Sérgio Freire. (2023) A smart and flexible approach for aggregation of adjacent polygons to meet a minimum target area or attribute value. Scientific Reports 13:1.
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Wendy K. Tam Cho & Bruce E. Cain. (2023) AI and Redistricting: Useful Tool for the Courts or Another Source of Obfuscation?. The Forum 20:3-4, pages 395-408.
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Callum Evans & Hugo Barbosa. 2023. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Machine Learning and Principles and Practice of Knowledge Discovery in Databases 167 180 .
Austin Buchanan. 2020. Encyclopedia of Optimization. Encyclopedia of Optimization 1 13 .
Hugo A. Akitaya, Matthew D. Jones, Matias Korman, Oliver Korten, Christopher Meierfrankenfeld, Michael J. Munje, Diane L. Souvaine, Michael Thramann & Csaba D. Tóth. (2022) Reconfiguration of connected graph partitions. Journal of Graph Theory 102:1, pages 35-66.
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Salvatore Saporito & Daniel Maliniak. (2022) Using the areal unit segregation measure to identify racially “packed” and “cracked” legislative districts. Electoral Studies 80, pages 102526.
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Cory McCartan, Christopher T. Kenny, Tyler Simko, George GarciaIIIIII, Kevin Wang, Melissa Wu, Shiro Kuriwaki & Kosuke Imai. (2022) Simulated redistricting plans for the analysis and evaluation of redistricting in the United States. Scientific Data 9:1.
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Amariah Becker & Dara Gold. (2022) The gameability of redistricting criteria. Journal of Computational Social Science 5:2, pages 1735-1777.
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Christian Haas, Peter Miller & Steven O. Kimbrough. (2022) An algorithmic approach to legislative apportionment bases and redistricting. Electoral Studies 79, pages 102520.
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Tiago Almeida & Vasco Manquinho. (2022) Constraint-based electoral districting using a new compactness measure: An application to Portugal. Computers & Operations Research 146, pages 105892.
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Elle Najt, Daryl DeFord & Justin Solomon. (2021) Empirical sampling of connected graph partitions for redistricting. Physical Review E 104:6.
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Amariah BeckerMoon DuchinDara GoldSam Hirsch. (2021) Computational Redistricting and the Voting Rights Act. Election Law Journal: Rules, Politics, and Policy 20:4, pages 407-441.
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Christopher T. Kenny, Shiro Kuriwaki, Cory McCartan, Evan T. R. Rosenman, Tyler Simko & Kosuke Imai. (2021) The use of differential privacy for census data and its impact on redistricting: The case of the 2020 U.S. Census. Science Advances 7:41.
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Virgilio Pérez, Cristina Aybar & Jose M. Pavía. (2021) Spanish electoral archive. SEA database. Scientific Data 8:1.
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Hisam SabouniCameron Shelton. (2021) State Legislative Redistricting: The Effectiveness of Traditional Districting Principles in the 2010 Wave. Election Law Journal: Rules, Politics, and Policy 20:2, pages 198-214.
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Eric A. Autry, Daniel Carter, Gregory J. Herschlag, Zach Hunter & Jonathan C. Mattingly. (2021) Metropolized Multiscale Forest Recombination for Redistricting. Multiscale Modeling & Simulation 19:4, pages 1885-1914.
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Wendy K. Tam Cho & Yan Y. Liu. (2021) A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions. Statistics and Computing 31:1.
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Hugo A. Akitaya, Matias Korman, Oliver Korten, Diane L. Souvaine & Csaba D. Tóth. 2021. Algorithms and Complexity. Algorithms and Complexity 61 74 .
Joaquin Artes, Aaron Russell Kaufman, Brian Kelleher Richter & Jeffrey F. Timmons. (2022) Are Firms Gerrymandered?. SSRN Electronic Journal.
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Amariah Becker & Dara Gold. (2022) The Gameability of Redistricting Criteria. SSRN Electronic Journal.
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Bernard Grofman & Jonathan R. Cervas. (2020) The Terminology of Districting. SSRN Electronic Journal.
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