ACEPoly: A function to compute Massey's Polycentric Absolute...
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ACEPoly

R Documentation

A function to compute Massey's Polycentric Absolute Centralisation Index

Description

The absolute centralization index measures a group spatial distribution compared to the distribution of land area around the city center. The function can be used in two ways: to provide an area vector and a vector containing the distances between spatial units centroids and the central spatial unit or a external geographic information source (spatial object or shape file).

Usage

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

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.
`a`	- a numeric vector containing spatial unit areas
`dc`	- a numeric matrix containing the distances between spatial units centroids and the central spatial units
`center`	- a numeric vector giving the number of the spatial units that represent the centers 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).

Value

a numeric vector containing asolute centralisation index value for each group

References

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

Examples

x <- segdata@data[ ,1:2]
ar<-area(segdata)
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'segdata'

ACEPoly(x, spatobj = segdata, center = c(28, 83) )

ACEPoly(x, folder = foldername, shape = shapename, center = c(28, 83))

center <- c(28, 83)
polydist <- matrix(data = NA, nrow = nrow(x), ncol = length(center))
for (i in 1:ncol(polydist))
  polydist[,i] <- distcenter(spatobj = segdata, center = center[i])
ACEPoly(x, a = ar, dc = polydist)

distmin <- vector(length = nrow(x))
for (i in 1:nrow(polydist)) distmin[i] <- min(polydist[i,])
ACE(x, a = ar, dc = distmin)

OasisR documentation built on Aug. 30, 2023, 1:09 a.m.