scorers: Scoring functions for 'redist_shortburst'

In redist: Simulation Methods for Legislative Redistricting

Scoring functions for redist_shortburst

Description

The output of these functions may be passed into redist_shortburst() as score_fn. Scoring functions have type redist_scorer and may be combined together using basic arithmetic operations.

Usage

scorer_group_pct(map, group_pop, total_pop, k = 1)

scorer_pop_dev(map)

scorer_splits(map, counties)

scorer_multisplits(map, counties)

scorer_frac_kept(map)

scorer_polsby_popper(map, perim_df = NULL, areas = NULL, m = 1)

scorer_status_quo(map, existing_plan = get_existing(map))

Arguments

map	A redist_map object.
group_pop	A numeric vector with the population of the group for every precinct.
total_pop	A numeric vector with the population for every precinct.
k	the k-th from the top group fraction to return as the score.
counties	A numeric vector with an integer from 1:n_counties
perim_df	perimeter distance dataframe from redist.prep.polsbypopper
areas	area of each precinct (ie st_area(map))
m	the m-th from the bottom Polsby Popper to return as the score. Defaults to 1, the minimum Polsby Popper score
existing_plan	A vector containing the current plan.

Details

Function details:

• scorer_group_pct returns the k-th top group percentage across districts. For example, if the group is Democratic voters and k=3, then the function returns the 3rd-highest fraction of Democratic voters across all districts. Can be used to target k VRA districts or partisan gerrymanders.

• scorer_pop_dev returns the maximum population deviation within a plan. Smaller values are closer to population parity, so use maximize=FALSE with this scorer.

• scorer_splits returns the fraction of counties that are split within a plan. Higher values have more county splits, so use maximize=FALSE with this scorer.

• scorer_frac_kept returns the fraction of edges kept in each district. Higher values mean more compactness.

• scorer_polsby_popper returns the m-th Polsby Popper score within a plan. Higher scores correspond to more compact districts. Use m=ndists/2 to target the median compactness, m=1 to target the minimum compactness.

• scorer_status_quo returns 1 - the rescaled variation of information distance between the plan and the existing_plan. Larger values indicate the plan is closer to the existing plan.

Value

A scoring function of class redist_scorer. single numeric value, where larger values are better for frac_kept, group_pct, and polsby_popper and smaller values are better for splits and pop_dev.

Examples

data(iowa)
iowa_map <- redist_map(iowa, existing_plan = cd_2010, pop_tol = 0.05, total_pop = pop)

scorer_frac_kept(iowa_map)
scorer_status_quo(iowa_map)
scorer_group_pct(iowa_map, dem_08, tot_08, k = 2)
1.5*scorer_frac_kept(iowa_map) + 0.4*scorer_status_quo(iowa_map)
1.5*scorer_frac_kept(iowa_map) + scorer_frac_kept(iowa_map)*scorer_status_quo(iowa_map)

redist documentation built on April 3, 2023, 5:46 p.m.