| name | redistricting-analysis |
| description | Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name. |
Redistricting Analysis with the redistverse
A comprehensive reference for redistricting analysis in R using the redistverse ecosystem (library(redistverse) loads redist, redistmetrics, ggredist, geomander, sf, and adj).
Standard Analysis Pipeline
- Load data — Download pre-built precinct map + demographics + elections via
alarmdata, or assemble your own sf object and build a redist_map. → 12-alarmdata.md
- Prepare adjacency — Verify and edit the adjacency graph (remove water-body edges, fix topological errors). → 08-adj.md, 09-geomander-adjacency.md
- Set constraints — Define population tolerance, county-split penalties, VRA hinge constraints, compactness. → 02-redist-constraints.md
- Simulate — Run
redist_smc() (recommended) or MCMC to generate an ensemble of valid plans. → 01-redist-simulation.md
- Validate — Check convergence (
summary()), R-hat, effective sample size, and plan diversity. → 01-redist-simulation.md
- Score — Compute compactness, partisan fairness, splits, and other metrics across the ensemble. → 04–06 redistmetrics references
- Visualize & compare — Map plans, plot metric distributions, compare enacted plan to the baseline. → 07-ggredist.md
Quick Navigation
| Package / Topic | Reference |
|---|
redist_map, redist_smc, redist_mergesplit, redist_flip, redist_plans, diagnostics | 01-redist-simulation.md |
redist_constr, add_constr_splits, add_constr_grp_hinge, all soft constraints | 02-redist-constraints.md |
redist_enumpart, redist_shortburst, redist_cyclewalk, init_particles | 03-redist-advanced.md |
redistmetrics — Polsby-Popper, Reock, spanning tree, prep_perims, comp_* functions | 04-redistmetrics-compactness.md |
redistmetrics — efficiency gap, mean-median, bias, declination, part_* functions | 05-redistmetrics-partisan.md |
redistmetrics — county splits, segregation, competitiveness, incumbents, plan_parity, group_frac | 06-redistmetrics-other.md |
ggredist — geom_district, party color scales, cartographic palettes, theme_map | 07-ggredist.md |
adj — adjacency graph construction, edge operations, coloring, Laplacian | 08-adj.md |
geomander — adjacency construction, contiguity checks, seam_rip, edge editing | 09-geomander-adjacency.md |
geomander — geo_match, estimate_down/up, block2prec, spatial estimation | 10-geomander-spatial.md |
Key Data Structures
redist_map — an sf tibble with one row per precinct. Stores the adjacency graph, population column, number of districts, and population tolerance. Created by redist_map() or downloaded via alarm_50state_map(). Standard columns include pop, pop_black, pop_hisp, pop_asian, pop_white, pop_vap, pop_bvap, ndv (Democratic votes), nrv (Republican votes), and geometry.
redist_plans — a tibble with one row per district per plan (so nsims × ndists rows, plus reference plans). Stores district assignments in a hidden integer matrix; metrics are added as columns via mutate(). Access the plan matrix with get_plans_matrix().
adj — an S3 vector class representing an adjacency list. Each element is a zero-indexed integer vector of neighbors. Stored as the adj column in redist_map.
Population Tolerance Guidelines
| Map type | Typical pop_tol | Legal basis |
|---|
| Congressional | 0.005 (±0.5%) | Wesberry v. Sanders |
| State legislative | 0.05 (±10%) | Reynolds v. Sims |
| Local | Varies by state | State law |
