Cluster spatial data with REDCAP (REgionalization with Dynamically Constrained Agglomerative clustering and Partitioning) routines.
scl_redcap(
xy,
dmat,
ncl,
full_order = TRUE,
linkage = "single",
shortest = TRUE,
nnbs = 6L,
iterate_ncl = FALSE,
quiet = FALSE
)Rectangular structure (matrix, data.frame, tibble), containing coordinates of points to be clustered.
Square structure (matrix, data.frame, tibble) containing
distances or equivalent metrics between all points in xy. If xy
has n rows, then dat must have n rows and n
columns.
Desired number of clusters. See description of `ncl_iterate` parameter for conditions under which actual number may be less than this value.
If FALSE, build spanning trees from first-order
relationships only, otherwise build from full-order relationships (see Note).
One of "single", "average", or
"complete"; see Note.
If TRUE, the dmat is interpreted as distances
such that lower values are preferentially selected; if FALSE, then
higher values of dmat are interpreted to indicate stronger
relationships, as is the case for example with covariances.
Number of nearest neighbours to be used in calculating clustering
trees. Triangulation will be used if nnbs <= 0.
Actual numbers of clusters found may be less than the specified value of `ncl`, because clusters formed from < 3 edges are removed. If `iterate_ncl = FALSE` (the default), the value is returned with whatever number of actual clusters is found. Setting this parameter to `TRUE` forces the algorithm to iterate until the exact number of clusters has been found. For large data sets, this may result in considerable longer calculation times.
If `FALSE` (default), display progress information on screen.
A object of class scl with tree containing the
clustering scheme, and xy the original coordinate data of the
clustered points. An additional component, tree_rest, enables the tree
to be re-cut to a different number of clusters via scl_recluster,
rather than calculating clusters anew.
Please refer to the original REDCAP paper ('Regionalization with
dynamically constrained agglomerative clustering and partitioning (REDCAP)',
by D. Guo (2008), Int.J.Geo.Inf.Sci 22:801-823) for details of the
full_order and linkage parameters. This paper clearly
demonstrates the general inferiority of spanning trees constructed from
first-order relationships. It is therefore strongly recommended that the
default full_order = TRUE be used at all times.
Other clustering_fns:
scl_full(),
scl_recluster()
n <- 100
xy <- matrix (runif (2 * n), ncol = 2)
dmat <- matrix (runif (n ^ 2), ncol = n)
scl <- scl_redcap (xy, dmat, ncl = 4)
# Those clusters will by default be constructed by connecting edges with the
# lowest (\code{shortest}) values of \code{dmat}, and will differ from
scl <- scl_redcap (xy, dmat, ncl = 4, shortest = FALSE)
# using 'full_order = FALSE' constructs clusters from first-order
# relationships only; not recommended, but possible nevertheless:
scl <- scl_redcap (xy, dmat, ncl = 4, full_order = FALSE)