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

Description

Relative Centralisation Index measures the proportion of a group that should change localisation to obtain the same level of centralisation that another group. The function can be used in two ways: by providing a vector with the distances to the center or a geographic source (spatial object or shape file) wich will be used to compute the vector within the function. The center parameter is necessary to specify the number of the spatial unit representing the center.

Usage

RCE(x, 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 distances from the spatial units cetroids to the center

center

- a value giving the number of the spatial unit that represents the zones'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 matrix with Relative 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]
distc<- distcenter(GreHSize, center = 19)
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'GreHSize'

RCE(x, dc=distc)

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

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