Hi all,
Our next virtual meeting will be at 12pm (EST) Wednesday, November 11,
where we will hear Cory McCartan (Harvard University) presents research on
"Sequential Monte Carlo for Sampling Balanced and Compact Redistricting
Plans."
*Abstract*:
Random sampling of graph partitions under constraints has become a popular
tool for evaluating legislative redistricting plans. Analysts detect
partisan gerrymandering by comparing a proposed redistricting plan with an
ensemble of sampled alternative plans. For successful application, sampling
methods must scale to large maps with many districts, incorporate realistic
legal constraints, and accurately sample from a selected target
distribution. Unfortunately, most existing methods struggle in at least one
of these three areas. We present a new Sequential Monte Carlo (SMC)
algorithm that draws representative redistricting plans from a realistic
target distribution of choice. Because it yields nearly independent
samples, the SMC algorithm can efficiently explore the relevant space of
redistricting plans than the existing Markov chain Monte Carlo algorithms
that yield dependent samples. Our algorithm can simultaneously incorporate
several constraints commonly imposed in real-world redistricting problems,
including equal population, compactness, and preservation of administrative
boundaries. We validate the accuracy of the proposed algorithm by using a
small map where all redistricting plans can be enumerated. We then apply
the SMC algorithm to evaluate the partisan implications of several maps
submitted by relevant parties in a recent high-profile redistricting case
in the state of Pennsylvania. Open-source software is available for
implementing the proposed methodology.
Paper is available from here <https://arxiv.org/pdf/2008.06131.pdf>.
*Zoom link*:
https://harvard.zoom.us/j/99424949004?pwd=aWtPNFM3ZzFYbWxIMXNoZDlyUElVZz09
*Schedule of the workshop*:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Best,
Soichiro
--
Soichiro Yamauchi
PhD candidate
Harvard University
URL:
https://soichiroy.github.io/