| segregation_index | R Documentation |
redist.segcalc calculates the dissimilarity index of segregation (see
Massey & Denton 1987 for more details) for a specified subgroup under any
redistricting plan.
segregation_index(
map,
group_pop,
total_pop = map[[attr(map, "pop_col")]],
.data = cur_plans()
)
redist.segcalc(plans, group_pop, total_pop)
map |
a |
group_pop |
A vector of populations for some subgroup of interest. |
total_pop |
A vector containing the populations of each geographic unit. |
.data |
a |
plans |
A matrix of congressional district assignments or a redist object. |
redist.segcalc returns a vector where each entry is the
dissimilarity index of segregation (Massey & Denton 1987) for each
redistricting plan in algout.
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.
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)
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