redist.combine is used to combine successive runs of redist.flip into a single data object

redist.combine(savename, nloop, nthin, temper)

## Arguments

savename

The name (without the loop or .rds suffix) of the saved simulations.

nloop

The number of loops being combined. Savename must be non-null.

nthin

How much to thin the simulations being combined.

temper

Whether simulated tempering was used (1) or not (0) in the simulations. Default is 0.

## Value

redist.combine returns an object of class "redist". The object redist is a list that contains the following components (the inclusion of some components is dependent on whether tempering techniques are used):

plans

Matrix of congressional district assignments generated by the algorithm. Each row corresponds to a geographic unit, and each column corresponds to a simulation.

distance_parity

Vector containing the maximum distance from parity for a particular simulated redistricting plan.

mhdecisions

A vector specifying whether a proposed redistricting plan was accepted (1) or rejected (0) in a given iteration.

mhprob

A vector containing the Metropolis-Hastings acceptance probability for each iteration of the algorithm.

pparam

A vector containing the draw of the p parameter for each simulation, which dictates the number of swaps attempted.

constraint_pop

A vector containing the value of the population constraint for each accepted redistricting plan.

constraint_compact

A vector containing the value of the compactness constraint for each accepted redistricting plan.

constraint_segregation

A vector containing the value of the segregation constraint for each accepted redistricting plan.

constraint_vra

A vector containing the value of the vra constraint for each accepted redistricting plan.

constraint_similar

A vector containing the value of the similarity constraint for each accepted redistricting plan.

constraint_partisan

A vector containing the value of the partisan constraint for each accepted redistricting plan.

constraint_minority

A vector containing the value of the minority constraint for each accepted redistricting plan.

constraint_hinge

A vector containing the value of the hinge constraint for each accepted redistricting plan.

constraint_qps

A vector containing the value of the QPS constraint for each accepted redistricting plan.

beta_sequence

A vector containing the value of beta for each iteration of the algorithm. Returned when tempering is being used.

mhdecisions_beta

A vector specifying whether a proposed beta value was accepted (1) or rejected (0) in a given iteration of the algorithm. Returned when tempering is being used.

mhprob_beta

A vector containing the Metropolis-Hastings acceptance probability for each iteration of the algorithm. Returned when tempering is being used.

a redist object with entries combined

## Details

This function allows users to combine multiple successive runs of redist.flip into a single redist object for analysis.

## 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.

## Examples

# \donttest{
data(fl25)
data(fl25_enum)
init_plan <- fl25_enum$plans[, 5118] ## Run the algorithm set.seed(1) temp <- tempdir() # alg_253 <- redist.flip(adj = fl25_adj, total_pop = fl25$pop,