Package index • redist

Simulation Algorithm Implementations

Core functions to perform a redistricting simulation

redist_smc(): SMC Redistricting Sampler (McCartan and Imai 2023)

redist_mergesplit(): Merge-Split/Recombination MCMC Redistricting Sampler (Carter et al. 2019)

redist_mergesplit_parallel(): Parallel Merge-Split/Recombination MCMC Redistricting Sampler

redist_flip(): 'Flip' Markov Chain Monte Carlo Redistricting Simulation (Fifield et al. 2020)

redist_shortburst(): Redistricting Optimization through Short Bursts

redist_constr(): Set up constraints for sampling

add_constr_status_quo() add_constr_grp_pow() add_constr_grp_hinge() add_constr_grp_inv_hinge() add_constr_compet() add_constr_incumbency() add_constr_splits() add_constr_multisplits() add_constr_total_splits() add_constr_pop_dev() add_constr_segregation() add_constr_polsby() add_constr_fry_hold() add_constr_log_st() add_constr_edges_rem() add_constr_custom(): Sampling constraints

redist.crsg(): Redistricting via Compact Random Seed and Grow Algorithm

redist.mcmc.mpi(): MCMC Redistricting Simulator using MPI

redist.rsg(): Redistricting via Random Seed and Grow Algorithm

redist_flip_anneal(): Flip MCMC Redistricting Simulator using Simulated Annealing

Analysis Functions

Functions for analyzing simulation outputs

redist_plans(): A set of redistricting plans

summary(<redist_plans>): Diagnostic information on sampled plans

add_reference(): Add a reference plan to a set of plans

subset_sampled() subset_ref(): Subset to sampled or reference draws

get_plans_matrix() as.matrix(<redist_plans>): Extract the matrix of district assignments from a redistricting simulation

get_plans_weights() weights(<redist_plans>): Extract the sampling weights from a redistricting simulation.

number_by(): Renumber districts to match a quantity of interest

pullback(): Pull back plans to unmerged units

match_numbers(): Renumber districts to match an existing plan

tally_var(): Tally a variable by district

classify_plans(): Hierarchically classify a set of redistricting plans

compare_plans(): Make a comparison between two sets of plans

is_county_split(): Identify which counties are split by a plan

last_plan(): Extract the last plan from a set of plans

min_move_parity(): Calculates Sparse Population Moves to Minimize Population Deviation

plans_diversity(): Calculate the diversity of a set of plans

plot(<redist_classified>): Plot a plan classification

prec_assignment(): Extract the district assignments for a precinct across all simulated plans

prec_cooccurrence(): Compute a matrix of precinct co-occurrences

proj_distr() proj_avg() proj_contr(): Calculate Projective Distributions, Averages, and Contrasts for a Summary Statistic

rbind(<redist_plans>): Combine multiple sets of redistricting plans

distr_compactness() redist.compactness(): Calculate compactness measures for a set of plans

competitiveness() redist.competitiveness(): Compute Competitiveness

plan_distances() redist.distances(): Compute Distance between Partitions

redist.district.splits(): Counts the Number of Counties within a District

group_frac() redist.group.percent(): Calculate Group Proportion by District

partisan_metrics() redist.metrics(): Calculate gerrymandering metrics for a set of plans

redist.multisplits(): Counts the Number of Counties Split Between 3 or More Districts

muni_splits() redist.muni.splits(): Counts the Number of Municipalities Split Between Districts

redist.parity() plan_parity(): Calculates Maximum Deviation from Population Parity

segregation_index() redist.segcalc(): Segregation index calculation for MCMC redistricting.

county_splits() redist.splits(): Count County Splits

redist_ci() redist_smc_ci() redist_mcmc_ci(): Confidence Intervals for SMC and MCMC Estimates

Setup Helpers

Functions that help prepare data and select constraints

redist_map() as_redist_map(): Create a redist_map object.

get_adj() set_adj(): Get and set the adjacency graph from a redist_map object

get_existing(): Extract the existing district assignment from a redist_map object

get_pop_tol() set_pop_tol(): Get and set the population tolerance from a redist_map object

get_target(): Extract the target district population from a redist_map object

is_contiguous(): Check that a redist_map object is contiguous

merge_by(): Merge map units

plot(<redist_constr>): Visualize constraints

plot(<redist_map>): Plot a redist_map

redist.coarsen.adjacency(): Coarsen Adjacency List

redist.constraint.helper(): Create Constraints for SMC

redist.county.id(): Create County IDs

redist.county.relabel(): Relabel Discontinuous Counties

redist.find.target(): Find Majority Minority Remainder

redist.findparams(): Run parameter testing for redist_flip

freeze() redist.freeze(): Freeze Parts of a Map

make_cores() redist.identify.cores(): Identify Cores of a District (Heuristic)

redist.plot.penalty(): (Deprecated) Visualize Group Power Penalty

redist.reduce.adjacency(): Reduce Adjacency List

redist.sink.plan(): Sink Plans to 1:ndists

redist.subset(): Subset a shp

`*`(<redist_scorer>) `+`(<redist_scorer>) `-`(<redist_scorer>): Scoring function arithmetic

combine_scorers() cbind(<redist_scorer>): Combine scoring functions

scorer_group_pct() scorer_pop_dev() scorer_splits() scorer_multisplits() scorer_frac_kept() scorer_polsby_popper() scorer_status_quo(): Scoring functions for redist_shortburst

Plotting Tools

Functions for creating plots and maps

plot(<redist_map>): Plot a redist_map

plot(<redist_plans>): Summary plots for \link{redist_plans}

redist.diagplot(): Diagnostic plotting functionality for MCMC redistricting.

redist.plot.adj(): Creates a Graph Overlay

redist.plot.contr_pfdr(): Plot a Projective Contrast with positive False Discovery Rate (pFDR) Control

redist.plot.cores(): Plot Cores

redist.plot.distr_qtys(): Plot quantities by district

redist.plot.hist() hist(<redist_plans>): Plot a histogram of a summary statistic

redist.plot.majmin(): Majority Minority Plots

redist.plot.map(): Plot a Map

redist.plot.plans(): Plot a district assignment

redist.plot.scatter(): Scatter plot of plan summary statistics

redist.plot.trace(): Make a traceplot for a summary statistic

redist.plot.varinfo(): Static Variation of Information Plot

Data

Data included to help demonstrate capabilities

EPSG: EPSG Table

fl25: Florida 25 Precinct Shape File

fl250: Florida 250 Precinct Shape File

fl25_adj: Florida 25 Precinct File

fl25_enum: All Partitions of 25 Precincts into 3 Congressional Districts (No Population Constraint)

fl70: Florida 70 Precinct Shape File

iowa: Iowa County File

Post Processing Helpers

Functions that help setup outputs for easier use

redist.combine.mpi(): Combine successive runs of redist.mcmc.mpi

redist.ipw(): Inverse probability reweighting for MCMC Redistricting

redist.smc_is_ci(): (Deprecated) Confidence Intervals for Importance Sampling Estimates

redist.uncoarsen(): Uncoarsen a District Matrix

Enumeration Tools

Functions for more involved enumeration choices

redist.calc.frontier.size(): Calculate Frontier Size

redist.enumpart(): Enumerate All Parititions (Fifield et al. 2020)

redist.init.enumpart(): Initialize enumpart

redist.prep.enumpart(): Prepares a run of the enumpart algorithm by ordering edges

redist.read.enumpart(): Read Results from enumpart

redist.run.enumpart(): Runs the enumpart algorithm

Miscellaneous

Other functions

redist-package redist: redist: Simulation Methods for Legislative Redistricting

avg_by_prec(): Average a variable by precinct (Deprecated)

get_mh_acceptance_rate(): Extract the Metropolis Hastings Acceptance Rate

get_sampling_info(): Extract the sampling information from a redistricting simulation

pl(): Access the Current redist_plans() Object

plot(<redist_map>): Plot a redist_map

print(<redist_classified>): Print redist_classified objects

print(<redist_constr>): Generic to print redist_constr

print(<redist_map>): Generic to print redist_map

print(<redist_plans>): Print method for redist_plans

redist.adjacency(): Adjacency List functionality for redist

redist.dist.pop.overlap(): Compare the Population Overlap Across Plans at the District Level

redist.plot.wted.adj(): Plot Weighted Border Adjacency

redist.prec.pop.overlap(): Compare the Population Overlap Across Plans at the Precinct Level

redist.random.subgraph(): Return a random subgraph of a shape

redist.reorder(): Reorders district numbers

redist.wted.adj(): Create Weighted Adjacency Data

redist_quantile_trunc(): Helper function to truncate importance weights