scanstatistics (version 0.1.0)

flexible_zones: Computes the flexibly shaped zones as in Tango (2005).

Description

Given a matrix of \(k\) nearest neighbors and an adjacency matrix for the locations involved, produces the set of flexibly shaped zones as a list of integer vectors. The locations in these zones are all connected, in the sense that any location in the zone can be reached from another by traveling through adjacent locations within the zone.

Usage

flexible_zones(k_nearest, adjacency_matrix, .parallel = FALSE,
  .paropts = NULL)

Arguments

k_nearest

An integer matrix of the \(k\) nearest neighbors for each location. Each row corresponds to a location, with the first element of each row being the location itself. Locations should be encoded as integers.

adjacency_matrix

A boolean matrix, with element \((i,j)\) set to TRUE if location \(j\) is adjacent to location \(i\).

.parallel

if TRUE, apply function in parallel, using parallel backend provided by foreach

.paropts

a list of additional options passed into the foreach function when parallel computation is enabled. This is important if (for example) your code relies on external data or packages: use the .export and .packages arguments to supply them so that all cluster nodes have the correct environment set up for computing.

Value

A list of integer vectors.

References

Tango, T. & Takahashi, K. (2005), A flexibly shaped spatial scan statistic for detecting clusters, International Journal of Health Geographics 4(1).

Examples

# NOT RUN {
A <- matrix(c(0,1,0,0,0,0,
              1,0,1,0,0,0,
              0,1,0,0,0,0,
              0,0,0,0,1,0,
              0,0,0,1,0,0,
              0,0,0,0,0,0), 
              nrow = 6, byrow = TRUE) == 1
nn <- matrix(as.integer(c(1,2,3,4,5,6,
                          2,1,3,4,5,6,
                          3,2,1,4,5,6,
                          4,5,1,6,3,2,
                          5,4,6,1,3,2,
                          6,5,4,1,3,2)),
                          nrow = 6, byrow = TRUE)
flexible_zones(nn, A)
# }