This is the implementation of the spatial decomposition of the Gini coefficient introduced by Rey and Smith (2013). The function calculates the global Gini and the two components of the spatial Gini: the inequality among nearest (geographically) neighbours and the inequality of non-neighbours. Three weighted schemes are currently supported: binary, bi-square and row standardised bi-square.
Usage
spGini(Coords, Bandwidth, x, WType = 'Binary')
Value
Returns a list of five values Gini, gwGini, nsGini, gwGini.frac, nsGini.frac
Gini
Global Gini
gwGini
First component of the spatial Gini: the inequality among nearest (geographically) neighbours
nsGini
Second component of the spatial Gini: the inequality among non-neighbours
gwGini.frac
The fraction of the first component of the spatial Gini
nsGini.frac
The fraction of the second component of the spatial Gini
Arguments
Coords
a numeric matrix or vector or data frame of two columns giving the X,Y coordinates of the observations (data points or geometric / population weighted centroids)
Bandwidth
a positive integer that defines the number of nearest neighbours for the calculation of the weights
x
a numeric vector of a variable
WType
a string giving the weighting scheme used to compute the weights matrix.
Options are: "Binary", "Bi-square", "RSBi-square". Default is "Binary".
Binary: weight = 1 for distances less than or equal to the distance of the furthest neighbour (H), 0 otherwise;
Bi-square: weight = (1-(ndist/H)^2)^2 for distances less than or equal to H, 0 otherwise;
RSBi-square: weight = Bi-square weights / sum (Bi-square weights) for each row in the weights matrix
Author
Stamatis Kalogirou <stamatis.science@gmail.com>
References
Rey, S.J., Smith, R. J. (2013) A spatial decomposition of the Gini coefficient, Letters in Spatial and Resource Sciences, 6 (2), pp. 55-70.