Analyze U.S. electoral district plans in R with redistverse. Guides data preparation, simulations under population and geographic constraints, diagnostic checks, and comparisons of district shape, partisan fairness, and administrative splits through maps and summary tables.
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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.
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A comprehensive reference for redistricting analysis in R using the redistverse ecosystem (library(redistverse) loads redist, redistmetrics, ggredist, geomander, sf, and adj).
alarmdata, or assemble your own sf object and build a redist_map. → 12-alarmdata.mdredist_smc() (recommended) or MCMC to generate an ensemble of valid plans. → 01-redist-simulation.mdsummary()), R-hat, effective sample size, and plan diversity. → 01-redist-simulation.md| 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 |
geomander — downloading VEST, ALARM, DRA, HEDA, get_lewis election data | 11-geomander-data.md |
alarmdata — alarm_50state_map, pre-built datasets, caching, alarm_add_plan | 12-alarmdata.md |
PL94171 — Census P.L. 94-171 decennial data ingestion | 13-pl94171.md |
censable (data + state IDs), easycensus (ACS), tinytiger (TIGER shapefiles) | 14-census-utilities.md |
baf — download official Census Bureau block assignment files | 15-baf.md |
rict — gt summary tables: population, demographics, elections, compactness, splits | 16-rict.md |
redistio — interactive Shiny plan drawing (draw()) and adjacency editor (adj_editor()) | 17-redistio.md |
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.
| 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 |
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Turn a broad research idea into clear, testable questions. Compare familiar and less conventional approaches, structure the selected question around its population and methods, and assess variables, feasibility, and potential theoretical contributions.
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Helps build a research framework by comparing theories, mapping relationships between variables, and deriving testable hypotheses. Explores less conventional options, examines weaknesses and competing explanations, and produces diagrams with anticipated reviewer objections.
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Clarify the philosophical assumptions behind a research project and check whether they fit the proposed methods. Get a reasoned research stance, draft proposal wording, and guidance for explaining how the researcher's background and values shape the study.
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Plan and draft academic papers through specialized agent roles covering literature, arguments, citations, and review. Get chapter guidance, revision roadmaps, Traditional Chinese and English abstracts, and documents formatted as LaTeX, DOCX, PDF, or Markdown.
中文简介正在准备中。当前显示英语简介。
Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.
中文简介正在准备中。当前显示英语简介。
Simulate academic peer review through five reviewer roles tailored to the paper's field. Receive separate critiques, an editorial decision, and a prioritized revision roadmap, or check whether a revised manuscript addresses earlier comments.
中文简介正在准备中。当前显示英语简介。