Closed christopherkenny closed 2 years ago
In Maryland, districts must:
We enforce a maximum population deviation of 0.5%.
Data for Maryland comes from the ALARM Project's 2020 Redistricting Data Files.
No manual pre-processing decisions were necessary.
We sample 5,000 districting plans for Maryland across 2 independent runs of the SMC algorithm. No special techniques were needed to produce the sample.
SMC: 5,000 sampled plans of 8 districts on 2,042 units `adapt_k_thresh`=0.985 • `seq_alpha`=0.5 `est_label_mult`=1 • `pop_temper`=0 Plan diversity 80% range: 0.49 to 0.78 R-hat values for summary statistics: pop_overlap total_vap plan_dev comp_edge comp_polsby pop_hisp 1.0205068 1.0031847 1.0026922 1.0018201 1.0021193 1.0076208 pop_white pop_black pop_aian pop_asian pop_nhpi pop_other 1.0057755 1.0173884 1.0045380 1.0055871 1.0129847 0.9998311 pop_two vap_hisp vap_white vap_black vap_aian vap_asian 1.0330381 1.0058124 1.0073100 1.0162325 1.0067133 1.0053799 vap_nhpi vap_other vap_two pre_16_rep_tru pre_16_dem_cli uss_16_rep_sze 1.0201413 1.0005733 1.0271314 1.0024141 1.0125128 1.0033708 uss_16_dem_van uss_18_rep_cam uss_18_dem_car gov_18_rep_hog gov_18_dem_jea atg_18_rep_wol 1.0112053 1.0035371 1.0098955 1.0051524 1.0152211 1.0011091 atg_18_dem_fro pre_20_dem_bid pre_20_rep_tru arv_16 adv_16 arv_18 1.0085301 1.0032436 1.0062913 1.0014592 1.0120006 1.0056666 adv_18 arv_20 adv_20 county_splits muni_splits ndv 1.0097472 1.0062913 1.0032436 1.0132886 1.0177737 1.0095900 nrv ndshare e_dvs pr_dem e_dem pbias 1.0016500 1.0070707 1.0070875 1.0127817 1.0138223 1.0032670 egap 1.0155451 Sampling diagnostics for SMC run 1 of 2 (2,500 samples) Eff. samples (%) Acc. rate Log wgt. sd Max. unique Est. k Split 1 2,456 (98.3%) 9.8% 0.27 1,600 (101%) 8 Split 2 2,427 (97.1%) 14.4% 0.34 1,561 ( 99%) 5 Split 3 2,386 (95.4%) 17.2% 0.45 1,551 ( 98%) 4 Split 4 2,358 (94.3%) 20.0% 0.51 1,536 ( 97%) 3 Split 5 2,305 (92.2%) 17.7% 0.55 1,542 ( 98%) 3 Split 6 2,256 (90.2%) 21.4% 0.61 1,480 ( 94%) 2 Split 7 2,234 (89.4%) 7.3% 0.60 1,325 ( 84%) 2 Resample 1,563 (62.5%) NA% 0.63 1,390 ( 88%) NA Sampling diagnostics for SMC run 2 of 2 (2,500 samples) Eff. samples (%) Acc. rate Log wgt. sd Max. unique Est. k Split 1 2,457 (98.3%) 13.2% 0.27 1,578 (100%) 6 Split 2 2,424 (97.0%) 17.8% 0.35 1,586 (100%) 4 Split 3 2,395 (95.8%) 17.2% 0.43 1,561 ( 99%) 4 Split 4 2,326 (93.0%) 13.0% 0.52 1,540 ( 97%) 5 Split 5 2,293 (91.7%) 18.5% 0.56 1,513 ( 96%) 3 Split 6 2,293 (91.7%) 20.2% 0.57 1,436 ( 91%) 2 Split 7 2,271 (90.8%) 7.0% 0.57 1,303 ( 82%) 2 Resample 1,641 (65.6%) NA% 0.58 1,438 ( 91%) NA • Watch out for low effective samples, very low acceptance rates (less than 1%), large std. devs. of the log weights (more than 3 or so), and low numbers of unique plans. R-hat values for summary statistics should be between 1 and 1.05.
TODO
enforce_style()
redist_map
redist_plans
@CoryMcCartan
Redistricting requirements
In Maryland, districts must:
Interpretation of requirements
We enforce a maximum population deviation of 0.5%.
Data Sources
Data for Maryland comes from the ALARM Project's 2020 Redistricting Data Files.
Pre-processing Notes
No manual pre-processing decisions were necessary.
Simulation Notes
We sample 5,000 districting plans for Maryland across 2 independent runs of the SMC algorithm. No special techniques were needed to produce the sample.
Validation
Checklist
TODO
lines from the template code have been removedenforce_style()
to format my coderedist_map
andredist_plans
objects, and summary statistics) have been edited@CoryMcCartan