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Random sampling of graph partitions under constraints has become a popular tool for evaluating legislative redistricting plans.
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., and Bürkner, P.-C. (2019) · 1903
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Complexity and geometry of sampling connected graph partitions
Najt, L., Deford, D., and Solomon, J. (2019) · 1908
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A merge-split proposal for reversible Monte Carlo Markov chain sampling of redistricting plans
Carter, D., Herschlag, G., Hunter, Z., and Mattingly, J. (2019) · 1911
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Spanning trees in random regular graphs
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Graph Theory
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The dimensions of residential segregation
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Generating random spanning trees more quickly than the cover time
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Rejection control and sequential importance sampling
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An optimization based heuristic for political districting
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Assessing South Carolina’s 1990s congressional districting
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Sequential Monte Carlo methods in practice
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A theoretical framework for sequential importance sampling with resampling
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Redistricting in a GIS environment: An optimisation algorithm using switching-points
Macmillan, W. (2001) · 2001
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A tabu search heuristic and adaptive memory procedure for political districting
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A sequential particle algorithm that keeps the particle system alive
LeGland, F. and Oudjane, N. (2005) · 2005
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Del Moral, P., Doucet, A., and Jasra, A. (2006) · 2006
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Ionides, E. L. (2008) · 2008
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Three applications of entropy to gerrymandering
Guth, L., Nieh, A., and Weighill, T. (2020) · 2010
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On sequential monte carlo, partial rejection control and approximate bayesian computation
Peters, G. W., Fan, Y., and Sisson, S. A. (2012) · 2012
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Sampling from complicated and unknown distributions: Monte Carlo and Markov chain Monte Carlo methods for redistricting
Cho, W. K. T. and Liu, Y. Y. (2018) · 2018
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Outlier analysis for Pennsylvania congressional redistricting
Duchin, M. (2018) · 2018
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178 A. 3d 737 (Pa: Supreme Court)
League of Women Voters v. Commonwealth (2018) · 2018
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Variance estimation in the particle filter
Lee, A. and Whiteley, N. (2018) · 2018
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A new approach for developing neutral redistricting plans
Magleby, D. B. and Mosesson, D. B. (2018) · 2018
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Understanding our Markov Chain significance test: A reply to Cho and Rubinstein-Salzedo
Chikina, M., Frieze, A., and Pegden, W. (2019) · 2019
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Numerically stable online estimation of variance in particle filters
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