redist (version 4.2.0)

segregation_index: Segregation index calculation for MCMC redistricting.

Description

redist.segcalc calculates the dissimilarity index of segregation (see Massey & Denton 1987 for more details) for a specified subgroup under any redistricting plan.

Usage

segregation_index(
  map,
  group_pop,
  total_pop = map[[attr(map, "pop_col")]],
  .data = cur_plans()
)
redist.segcalc(plans, group_pop, total_pop)

Value

redist.segcalc returns a vector where each entry is the dissimilarity index of segregation (Massey & Denton 1987) for each redistricting plan in algout.

Arguments

map

a redist_map object

group_pop

A vector of populations for some subgroup of interest.

total_pop

A vector containing the populations of each geographic unit.

.data

a redist_plans object

plans

A matrix of congressional district assignments or a redist object.

References

Fifield, Benjamin, Michael Higgins, Kosuke Imai and Alexander Tarr. (2016) "A New Automated Redistricting Simulator Using Markov Chain Monte Carlo." Working Paper. Available at http://imai.princeton.edu/research/files/redist.pdf.

Massey, Douglas and Nancy Denton. (1987) "The Dimensions of Social Segregation". Social Forces.

Examples

# \donttest{
data(fl25)
data(fl25_enum)
data(fl25_adj)

## Get an initial partition
init_plan <- fl25_enum$plans[, 5118]
fl25$init_plan <- init_plan

## 25 precinct, three districts - no pop constraint ##
fl_map <- redist_map(fl25, existing_plan = 'init_plan', adj = fl25_adj)
alg_253 <- redist_flip(fl_map, nsims = 10000)


## Get Republican Dissimilarity Index from simulations
# old: rep_dmi_253 <- redist.segcalc(alg_253, fl25$mccain, fl25$pop)
rep_dmi_253 <- seg_dissim(alg_253, fl25, mccain, pop)  |>
    redistmetrics::by_plan(ndists = 3)
# }