RCL {OasisR} | R 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 the 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')