Simulation Methods for Legislative Redistricting
Add a reference plan to a set of plans
Average a variable by precinct (Deprecated)
Hierarchically classify a set of redistricting plans
Make a comparison between two sets of plans
Sampling constraints
Get and set the adjacency graph from a redist_map object
Extract the existing district assignment from a redist_map object
Extract the Metropolis Hastings Acceptance Rate
Extract the matrix of district assignments from a redistricting simula...
Extract the sampling weights from a redistricting simulation.
Get and set the population tolerance from a redist_map object
Extract the sampling information from a redistricting simulation
Extract the target district population from a redist_map object
Check that a redist_map object is contiguous
Identify which counties are split by a plan
Extract the last plan from a set of plans
Renumber districts to match an existing plan
Merge map units
Calculates Sparse Population Moves to Minimize Population Deviation
Renumber districts to match a quantity of interest
Access the Current redist_plans() Object
Calculate the diversity of a set of plans
Plot a plan classification
Visualize constraints
Plot a redist_map
Summary plots for \link{redist_plans}
Extract the district assignments for a precinct across all simulated p...
Compute a matrix of precinct co-occurrences
Print redist_classified objects
Generic to print redist_constr
Generic to print redist_map
Print method for redist_plans
Calculate Projective Distributions, Averages, and Contrasts for a Summ...
Pull back plans to unmerged units
Combine multiple sets of redistricting plans
Confidence Intervals for SMC and MCMC Estimates
Set up constraints for sampling
Flip MCMC Redistricting Simulator using Simulated Annealing
'Flip' Markov Chain Monte Carlo Redistricting Simulation (Fifield et a...
Create a redist_map object.
Parallel Merge-Split/Recombination MCMC Redistricting Sampler
Merge-Split/Recombination MCMC Redistricting Sampler (Carter et al. 20...
A set of redistricting plans
Helper function to truncate importance weights
Redistricting Optimization through Short Bursts
SMC Redistricting Sampler (McCartan and Imai 2023)
redist: Simulation Methods for Legislative Redistricting
Adjacency List functionality for redist
Calculate Frontier Size
Coarsen Adjacency List
Combine successive runs of redist.mcmc.mpi
Calculate compactness measures for a set of plans
Compute Competitiveness
Create Constraints for SMC
Create County IDs
Relabel Discontinuous Counties
Redistricting via Compact Random Seed and Grow Algorithm
Diagnostic plotting functionality for MCMC redistricting.
Compare the Population Overlap Across Plans at the District Level
Compute Distance between Partitions
Counts the Number of Counties within a District
Enumerate All Parititions (Fifield et al. 2020)
Find Majority Minority Remainder
Run parameter testing for redist_flip
Freeze Parts of a Map
Calculate Group Proportion by District
Identify Cores of a District (Heuristic)
Initialize enumpart
Inverse probability reweighting for MCMC Redistricting
MCMC Redistricting Simulator using MPI
Calculate gerrymandering metrics for a set of plans
Counts the Number of Counties Split Between 3 or More Districts
Counts the Number of Municipalities Split Between Districts
Calculates Maximum Deviation from Population Parity
Creates a Graph Overlay
Plot a Projective Contrast with positive False Discovery Rate (pFDR) C...
Plot Cores
Plot quantities by district
Plot a histogram of a summary statistic
Majority Minority Plots
Plot a Map
(Deprecated) Visualize Group Power Penalty
Plot a district assignment
Scatter plot of plan summary statistics
Make a traceplot for a summary statistic
Static Variation of Information Plot
Plot Weighted Border Adjacency
Compare the Population Overlap Across Plans at the Precinct Level
Prepares a run of the enumpart algorithm by ordering edges
Return a random subgraph of a shape
Read Results from enumpart
Reduce Adjacency List
Reorders district numbers
Redistricting via Random Seed and Grow Algorithm
Runs the enumpart algorithm
Segregation index calculation for MCMC redistricting.
Sink Plans to 1:ndists
(Deprecated) Confidence Intervals for Importance Sampling Estimates
Count County Splits
Subset a shp
Uncoarsen a District Matrix
Create Weighted Adjacency Data
Objects exported from other packages
Scoring function arithmetic
Combine scoring functions
Scoring functions for redist_shortburst
Subset to sampled or reference draws
Diagnostic information on sampled plans
Tally a variable by district
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 the SMC algorithm of McCartan and Imai (2023) <doi:10.1214/23-AOAS1763>, the enumeration algorithm of Fifield, Imai, Kawahara, and Kenny (2020) <doi:10.1080/2330443X.2020.1791773>, the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) <doi:10.1080/10618600.2020.1739532>, the Merge-split/Recombination algorithms of Carter et al. (2019) <doi:10.48550/arXiv.1911.01503> and DeFord et al. (2021) <doi:10.1162/99608f92.eb30390f>, and the Short-burst optimization algorithm of Cannon et al. (2020) <doi:10.48550/arXiv.2011.02288>.