RCL: A function to compute the relative clustering index (RCL)

View source: R/SegFunctions.R

RCLR Documentation

A function to compute the relative clustering index (RCL)

Description

The relative clustering index, RCL, compares the mean proximity of a group to the mean proximity of another group. The function can be used in two ways: to provide a distance matrix or a external geographic information source (spatial object or shape file).

Usage

RCL(x, d = NULL, fdist = 'e', distin = 'm',  distout = 'm', diagval = '0', 
beta = 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.

d

- a matrix of the distances between spatial unit centroids

fdist

- the method used for distance interaction matrix: e' for inverse exponential function (by default) and 'l' for linear.

distin

- input metric conversion, based on bink package and includes conversions from 'm', 'km', 'inch', 'ft', 'yd', 'mi', 'naut_mi', etc.

distout

- output metric conversion, based on bink package and includes conversions to 'm', 'km', 'inch', 'ft', 'yd', 'mi', 'naut_mi', etc.

diagval

- when providing a spatial object or a shape file, the user has the choice of the spatial matrix diagonal definition: diagval = '0' (by default) for an null diagonal and diagval = 'a' to compute the diagonal as 0.6 * square root (spatial/organizational unitsarea) (White, 1983)

beta

- distance decay parameter

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 matrix containing relative clustering index values for each pair of groups

References

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

See Also

Proximity measures: Pxx, Pxy, Poo, SP

Clustering Indices: ACL

Examples

x <- segdata@data[ ,1:2]
ar<-area(segdata)
dist <- distance(segdata)
diag(dist)<-sqrt(ar) * 0.6
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'segdata'

RCL(x, spatobj = segdata)

RCL(x, folder = foldername, shape = shapename, fdist = 'l') 

RCL(x, spatobj = segdata, diagval ='a')

RCL(x, d = dist, fdist = 'e')


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

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