No manual pre-processing decisions were necessary.
Simulation Notes
We sample 5,000 districting plans for Oklahoma across 2 independent runs of the SMC algorithm.
We use a pseudo county constraint which uses counties, except for Oklahoma County which uses municipalities.
No special techniques were needed to produce the sample.
Validation
SMC: 5,000 sampled plans of 5 districts on 1,947 units
`adapt_k_thresh`=0.985 • `seq_alpha`=0.5
`est_label_mult`=1 • `pop_temper`=0
Plan diversity 80% range: 0.59 to 0.91
R-hat values for summary statistics:
pop_overlap total_vap plan_dev comp_edge comp_polsby pop_hisp pop_white pop_black pop_aian
1.0026971 1.0016413 0.9999266 1.0000279 1.0025800 1.0012320 1.0037122 1.0072595 1.0007859
pop_asian pop_nhpi pop_other pop_two vap_hisp vap_white vap_black vap_aian vap_asian
1.0035005 1.0008942 1.0004423 1.0002995 1.0010506 1.0035990 1.0075433 1.0005558 1.0023831
vap_nhpi vap_other vap_two pre_16_rep_tru pre_16_dem_cli uss_16_rep_lan uss_16_dem_wor gov_18_rep_sti gov_18_dem_edm
1.0010786 1.0000068 1.0000888 1.0005939 1.0011868 1.0010260 1.0034591 1.0007339 1.0004562
atg_18_rep_hun atg_18_dem_myl pre_20_rep_tru pre_20_dem_bid uss_20_rep_inh uss_20_dem_bro arv_16 adv_16 arv_18
1.0011417 1.0017219 1.0005910 1.0010144 1.0006824 1.0019222 1.0009923 1.0021257 1.0009233
adv_18 arv_20 adv_20 county_splits muni_splits ndv nrv ndshare e_dvs
1.0009864 1.0006110 1.0012889 1.0013199 1.0016048 1.0011041 1.0008314 1.0022144 1.0021898
e_dem pbias egap
0.9999422 1.0005190 1.0017663
Sampling diagnostics for SMC run 1 of 2 (2,500 samples)
Eff. samples (%) Acc. rate Log wgt. sd Max. unique Est. k
Split 1 2,454 (98.2%) 11.8% 0.27 1,588 (100%) 7
Split 2 2,416 (96.6%) 15.6% 0.38 1,559 ( 99%) 5
Split 3 2,386 (95.4%) 22.4% 0.42 1,524 ( 96%) 3
Split 4 2,352 (94.1%) 10.0% 0.47 1,368 ( 87%) 2
Resample 1,871 (74.8%) NA% 0.46 1,470 ( 93%) 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 2,454 (98.2%) 8.4% 0.27 1,567 ( 99%) 10
Split 2 2,413 (96.5%) 13.4% 0.38 1,566 ( 99%) 6
Split 3 2,335 (93.4%) 14.5% 0.49 1,517 ( 96%) 5
Split 4 2,304 (92.2%) 7.6% 0.51 1,400 ( 89%) 3
Resample 1,637 (65.5%) NA% 0.50 1,444 ( 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.
Redistricting requirements
In Oklahoma, districts must:
Interpretation of requirements
We enforce a maximum population deviation of 0.5%. We apply a county/municipality constraint, as described below.
Data Sources
Data for Oklahoma 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 Oklahoma across 2 independent runs of the SMC algorithm. We use a pseudo county constraint which uses counties, except for Oklahoma County which uses municipalities. 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