RCE: A function to compute Relatice Centralisation Index (RCE)

Description

The relative centralisation index measures the proportion of a group that should change its localization to achieve the same level of centralization as another group. The function can be used in two ways: to provide a vector containing the distances between spatial unit centroids or a external geographic information source (spatial object or shape file).

Usage

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

Value

a matrix containing relative centralisation index values

Arguments

x: - an object of class matrix (or which can be coerced to that class), where each column represents the distribution of a group within spatial units. The number of columns should be greater than 1 (at least 2 groups are required). You should not include a column with total population, because this will be interpreted as a group.
dc: - a numeric vector containing the distances between spatial units centroids and the central spatial unit
center: - a numeric value giving the number of the spatial unit that represents the center in the table
spatobj: - a spatial object (SpatialPolygonsDataFrame) with geographic information
folder: - a character vector with the folder (directory) name indicating where the shapefile is located on the drive
shape: - a character vector with the name of the shapefile (without the .shp extension).

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 <- segdata@data[ ,1:2]
distc<- distcenter(segdata, center = 28)
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'segdata'

RCE(x, dc=distc) 

RCE(x, spatobj = segdata, center = 28) 

RCE(x, folder = foldername, shape = shapename, center = 28)