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specify_clusters algorithmically assigns locations to clusters by grouping them geographically

Usage

specify_clusters(
  trial = trial,
  c = NULL,
  h = NULL,
  algorithm = "NN",
  reuseTSP = FALSE
)

Arguments

trial

A CRT object or data frame containing (x,y) coordinates of households

c

integer: number of clusters in each arm

h

integer: number of locations per cluster

algorithm

algorithm for cluster boundaries, with options:

NNNearest neighbour: assigns equal numbers of locations to each cluster
kmeanskmeans clustering: aims to partition locations so that each belongs to the cluster with the nearest centroid.
TSPtravelling salesman problem heuristic: Assigns locations sequentially along a travelling salesman path.
reuseTSP

logical: indicator of whether a pre-existing path should be used by the TSP algorithm

Value

A list of class "CRTsp" containing the following components:

geom_fulllist:summary statistics describing the site, and cluster assignments.
trialdata frame:rows correspond to geolocated points, as follows:
xnumeric vector: x-coordinates of locations
ynumeric vector: y-coordinates of locations
clusterfactor: assignments to cluster of each location
...other objects included in the input "CRTsp" object or data frame

Details

The reuseTSP parameter is used to allow the path to be reused for creating alternative allocations with different cluster sizes.

Either c or h must be specified. If both are specified the input value of c is ignored.

Examples

#Assign clusters of average size h = 40 to a test set of co-ordinates, using the kmeans algorithm
exampletrial <- specify_clusters(trial = readdata('exampleCRT.txt'),
                            h = 40, algorithm = 'kmeans', reuseTSP = FALSE)