redist_flip_anneal: Flip MCMC Redistricting Simulator using Simulated Annealing
In redist: Simulation Methods for Legislative Redistricting

redist_flip_anneal

R Documentation

Flip MCMC Redistricting Simulator using Simulated Annealing

Description

redist_flip_anneal simulates congressional redistricting plans using Markov chain Monte Carlo methods coupled with simulated annealing.

Usage

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
)

Arguments

`map`	A `redist_map` object.
`nsims`	The number of samples to draw, not including warmup.
`warmup`	The number of warmup samples to discard.
`init_plan`	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.
`constraints`	A `redist_constr` object.
`num_hot_steps`	The number of steps to run the simulator at beta = 0. Default is 40000.
`num_annealing_steps`	The number of steps to run the simulator with linearly changing beta schedule. Default is 60000
`num_cold_steps`	The number of steps to run the simulator at beta = 1. Default is 20000.
`eprob`	The probability of keeping an edge connected. The default is `0.05`.
`lambda`	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`.
`adapt_lambda`	Whether to adaptively tune the lambda parameter so that the Metropolis-Hastings acceptance probability falls between 20% and 40%. Default is FALSE.
`adapt_eprob`	Whether to adaptively tune the edgecut probability parameter so that the Metropolis-Hastings acceptance probability falls between 20% and 40%. Default is FALSE.
`exact_mh`	Whether to use the approximate (0) or exact (1) Metropolis-Hastings ratio calculation for accept-reject rule. Default is FALSE.
`maxiterrsg`	Maximum number of iterations for random seed-and-grow algorithm to generate starting values. Default is 5000.
`verbose`	Whether to print initialization statement. Default is `TRUE`.