redist.mcmc.anneal
simulates congressional redistricting plans
using Markov chain Monte Carlo methods coupled with simulated annealing.
redist.mcmc.anneal(adjobj, popvec, ndists,
initcds, num_hot_steps, num_annealing_steps,
num_cold_steps,
eprob, lambda, popcons, grouppopvec,
areasvec, countymembership, borderlength_mat,
ssdmat, constraint, constraintweights,
compactness_metric, rngseed, maxiterrsg,
adapt_lambda, adapt_eprob,
contiguitymap, exact_mh,
savename, verbose, ncores)
An adjacency matrix, list, or object of class "SpatialPolygonsDataFrame."
A vector containing the populations of each geographic unit
The numbe of congressional districts. The default is
NULL
.
A vector containing the congressional district labels
of each geographic unit. The default is NULL
. If not provided,
random and contiguous congressional district assignments will be generated
using redist.rsg
.
The number of steps to run the simulator at beta = 0. Default is 40000.
The number of steps to run the simulator with linearly changing beta schedule. Default is 60000
The number of steps to run the simulator at beta = 1. Default is 20000.
The probability of keeping an edge connected. The
default is 0.05
.
The parameter detmerining the number of swaps to attempt
each iteration fo the algoirhtm. The number of swaps each iteration is
equal to Pois(lambda
) + 1. The default is 0
.
The strength of the hard population
constraint. popcons
= 0.05 means that any proposed swap that
brings a district more than 5% away from population parity will be
rejected. The default is NULL
.
A vector of populations for some sub-group of
interest. The default is NULL
.
A vector of precinct areas for discrete Polsby-Popper.
The default is NULL
.
A vector of county membership assignments. The default is NULL
.
A matrix of border length distances, where
the first two columns are the indices of precincts sharing a border and
the third column is its distance. Default is NULL
.
A matrix of squared distances between geographic
units. The default is NULL
.
Which constraint to apply. Accepts any combination of compact
,
segregation
, population
, similarity
, or none
(no constraint applied). The default is NULL.
The weights to apply to each constraint. Should be a vector the same length as constraint. Default is NULL.
The compactness metric to use when constraining on
compactness. Default is fryer-holden
, the other implemented option
is polsby-popper
.
Allows the user to set the seed for the
simulations. Default is NULL
.
Maximum number of iterations for random seed-and-grow algorithm to generate starting values. Default is 5000.
Whether to adaptively tune the lambda parameter so that the Metropolis-Hastings acceptance probability falls between 20% and 40%. Default is FALSE.
Whether to adaptively tune the edgecut probability parameter so that the Metropolis-Hastings acceptance probability falls between 20% and 40%. Default is FALSE.
Use queens or rooks distance criteria for generating an adjacency list from a "SpatialPolygonsDataFrame" data type. Default is "rooks".
Whether to use the approximate (0) or exact (1) Metropolis-Hastings ratio calculation for accept-reject rule. Default is FALSE.
Filename to save simulations. Default is NULL
.
Whether to print initialization statement.
Default is TRUE
.
The number of cores available to parallelize over. Default is 1.