R/redist_flip.R
redist_flip_anneal.Rdredist_flip_anneal simulates congressional redistricting plans
using Markov chain Monte Carlo methods coupled with simulated annealing.
redist_flip_anneal(
map,
nsims,
warmup = 0,
init_plan = NULL,
constraints = redist_constr(),
num_hot_steps = 40000,
num_annealing_steps = 60000,
num_cold_steps = 20000,
eprob = 0.05,
lambda = 0,
adapt_lambda = FALSE,
adapt_eprob = FALSE,
exact_mh = FALSE,
maxiterrsg = 5000,
verbose = TRUE
)A redist_map object.
The number of samples to draw, not including warmup.
The number of warmup samples to discard.
A vector containing the congressional district labels
of each geographic unit. The default is NULL. If not provided,
a random initial plan will be generated using redist_smc. You can also
request to initialize using redist.rsg by supplying 'rsg', though this is
not recommended behavior.
A redist_constr object.
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 determining the number of swaps to attempt
each iteration of the algorithm. The number of swaps each iteration is
equal to Pois(lambda) + 1. The default is 0.
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.
Whether to use the approximate (0) or exact (1) Metropolis-Hastings ratio calculation for accept-reject rule. Default is FALSE.
Maximum number of iterations for random seed-and-grow algorithm to generate starting values. Default is 5000.
Whether to print initialization statement.
Default is TRUE.
redist_plans