`redist.combine`

is used to combine successive runs of `redist.flip`

into a single data object

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

- 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.

`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

This function allows users to combine multiple successive runs of
`redist.flip`

into a single `redist`

object for analysis.

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.

```
# \donttest{
data(fl25)
data(fl25_enum)
data(fl25_adj)
## Code to run the simulations in Figure 4 in Fifield, Higgins,Imai and Tarr (2015)
## Get an initial partition
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,
# init_plan = init_plan, nsims = 10000,
# nloop = 2, savename = paste0(temp, "/test"))
# out <- redist.combine(savename = paste0(temp, "/test"), nloop = 2, nthin = 10)
# }
```