ACE: A function to compute Absolute Centralisation Index (ACE)

Description

Absolute centralisation index measures the proportion of a group that should change localisation to obtain a uniform density around the area's center. The function can be used in two ways: by providing the area vector and the distances to the center vector or a geographic source (spatial object or shape file) wich will be used to compute the vectors within the function. The center parameter is necessary to specify the number of the spatial unit representing the center

Usage

ACE(x, a = NULL, dc = NULL, center = 1, spatobj = NULL, folder = NULL, shape = NULL)

Arguments

- 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

- a vector with areas of spatial units

- a vector with the distances between spatial units centroids and the center

center

- a value giving the number of the spatial unit that represents the zone's center

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 Centralisation index

References

Duncan O. D. and Duncan B. (1955) A Methodological Analysis of Segregation Indexes. American Sociological Review 41, pp. 210-217

Examples

Run this code

x <- slot(GreHSize, 'data')[ ,3:5]
ar<-area(GreHSize)
distc<- distcenter(GreHSize, center = 19)
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'GreHSize'

ACE(x, a = ar, dc=distc)

ACE(x, spatobj = GreHSize, center = 19)

ACE(x, folder = foldername, shape = shapename, center = 19)