OasisR (version 1.0.0)

ACL: A function to compute Absolute Clustering Index (ACL)

Description

The more contiguous spatial units a group occupies (forming an enclave within the zone) the more clustered and therefore segregated it is. The function can be used in two ways: by providing a contiguity matrix or a geographic source (spatial object or shape file) wich will be used to compute the matrix within the function

Usage

ACL(x, c = NULL, spatobj = NULL, folder = NULL, shape = NULL)

Arguments

x

- an object of class matrix (or that can be coerced to that class), where each column represents the distribution of a population group, within spatial units. The number of columns should be greater than one (at least two population groups are require

c

- a binary contiguity (adjacency) symetric matrix where each element Cij equals 1 if i-th and j-th spatial units are adjacent, 0 otherwise.

spatobj

- a spatial object (SpatialPolygonsDataFrame)

folder

- a character vector with the folder (directory) where the shapefile is

shape

- a character vector with the name of the shapefile (without the .shp extension)

Value

• A vector with Absolute Clustering index

References

Massey D. S. and Denton N. A. (1988) The dimensions of residential segregation. Social Forces 67(2), pp. 281-315.

See Also

Mean proximity between members of a group: Pxx Relative Clustering Index: RCL

Examples

x <- slot(GreHSize, 'data')[ ,3:5]
contiguity <- contig(GreHSize)
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'GreHSize'

ACL(x, c=contiguity)

ACL(x, spatobj = GreHSize)

ACL(x, folder = foldername, shape = shapename)