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redist (version 3.0.7)

Simulation Methods for Legislative Redistricting

Description

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 methods described in Fifield, Higgins, Imai and Tarr (2020) , Fifield, Imai, Kawahara, and Kenny (2020) , and McCartan and Imai (2020) .

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Version

Install

install.packages('redist')

Monthly Downloads

363

Version

3.0.7

License

GPL (>= 2)

Maintainer

Christopher T. Kenny

Last Published

May 15th, 2021

Functions in redist (3.0.7)

All Partitions of 25 Precincts into 3 Congressional Districts (No Population Constraint)

as.matrix.redist

Extract the redistricting matrix from a redist object

Make a comparison between two sets of plans

Florida 25 Precinct File

Add a reference plan to a set of plans

Hierarchically classify a set of redistricting plans

Get and set the adjacency graph from a redist_map object

Florida 25 Precinct Shape File

Florida 250 Precinct Shape File

get_sampling_info

Extract the sampling information from a redistricting simulation

print.redist_plans

Print method for redist_plans

Extract the target district population from a redist_map object

Check that a redist_map object is contiguous

Iowa County File

Confidence Intervals for Importance Sampling Estimates

plot.redist_plans

Summary plots for \link{redist_plans}

Renumber districts to match a quantity of interest

Get and set the population tolerance from a redist_map object

get_plans_weights

Extract the sampling weights from a redistricting simulation.

Merge map units

Florida 70 Precinct Shape File

flip_constraints_helper

Flip Constraints Helper

get_mh_acceptance_rate

Extract the Metropolis Hastings Acceptance Rate

get_plans_matrix

Extract the matrix of district assignments from a redistricting simulation

Extract the last plan from a set of plans

Renumber districts to match an existing plan

is_county_split

Identify which counties are split by a plan

plot.redist_classified

Plot a plan classification

Pull back plans to unmerged units

Extract the existing district assignment from a redist_map object

prec_cooccurrence

Compute a matrix of precinct co-occurrences

prec_assignment

Extract the district assignments for a precinct across all simulated plans

redist.enumpart

Enumerate All Parititions

redist.enumerate

Deprecated: Exact Redistricting Plan Enumerator

redist.calc.frontier.size

Calculate Frontier Size

redist.coarsen.adjacency

Coarsen Adjacency List

redist.choropleth

Creates a Choropleth

distr_compactness

Calculate compactness measures for a set of plans

Combine successive runs of redist.flip

Reorders district numbers

redist.plot.hist

Plot a histogram of a summary statistic

Identify Cores of a District (Heuristic)

redist.plot.majmin

Majority Minority Plots

redist.init.enumpart

Initialize enumpart

'Flip' Markov Chain Monte Carlo Redistricting Simulation

Redistricting via Random Seed and Grow Algorithm

Create a redist_map object.

competitiveness

Compute Competitiveness

Freeze Parts of a Map

Calculate Group Percent by District

plot.redist_map

Plot a redist_map

print.redist_map

Generic to print redist_map

print.redist_classified

Print redist_classified objects

redist.county.relabel

Relabel Discontinuous Counties

redist.adjacency

Adjacency List functionality for redist

Simulation Methods for Legislative Redistricting

Redistricting via Compact Random Seed and Grow Algorithm

redist.plot.cores

partisan_metrics

Calculate gerrymandering metrics for a set of plans

Scoring function arithmetic

redist.mcmc.mpi

MCMC Redistricting Simulator using MPI

redist.diagplot

Diagnostic plotting functionality for MCMC redistricting.

scorer_group_pct

Scoring functions for redist_shortburst

redist.prep.polsbypopper

Prep Polsby Popper Perimeter Dataframe

redist.plot.distr_qtys

Plot quantities by district

redist.smc_is_ci

Confidence Intervals for Importance Sampling Estimates

redist.random.subgraph

Return a random subgraph of a shape

redist_mergesplit

Merge-Split/Recombination MCMC Redistricting Sampler

redist.plot.scatter

Scatter plot of plan summary statistics

A set of redistricting plans

redist.sink.plan

Sink Plans to 1:ndists

redist.plot.plans

Plot a district assignment

segregation_index

Segregation index calculation for MCMC redistricting.

Count County Splits

redist_quantile_trunc

Helper function to truncate importance weights

redist_shortburst

Redistricting Optimization through Short Bursts

Print legacy redist objects

redist.county.id

Create County IDs

redist.find.target

Find Majority Minority Remainder

Calculates Maximum Deviation from Population Parity

redist.findparams

Run parameter testing for redist.flip

redist.constraint.helper

Create Constraints for SMC

Inverse probability reweighting for MCMC Redistricting

Creates a map with optional graph overlay

Compute Distance between Partitions

redist.uncoarsen

Uncoarsen a District Matrix

redist.plot.adj

Creates a Graph Overlay

redist.reduce.adjacency

Reduce Adjacency List

redist.read.enumpart

Read Results from enumpart

redist.prep.enumpart

Prepares a run of the enumpart algorithm by ordering edges

redist.plot.varinfo

Static Variation of Information Plot

redist.combine.mpi

Combine successive runs of redist.mcmc.mpi

redist.combine.anneal

redist.combine.anneal

MCMC Redistricting Simulator

redist.mcmc.anneal

MCMC Redistricting Simulator using Simulated Annealing

Subset to sampled or reference draws

redist.plot.map

redist.plot.penalty

Visualize VRA Penalty

redist.samplepart

DEFUNCT: Sample partitions using spanning trees

redist.run.enumpart

Runs the enumpart algorithm

Objects exported from other packages

SMC Redistricting Sampler