OasisR (version 1.0.0)

Morill: A function to compute Morill's segregation index

Description

Morill's segregation index develops Duncan's index by taking into account the interactions between spatial units (contiguity). The function can be used in two ways: by providing a contiguity matrix or a geographic source (spatial object or shape file) wich will be used to compute the contiguity matrix within the function

Usage

Morill(x, c = NULL, spatobj = NULL, folder = NULL, shape = NULL)

Arguments

x

- 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

c

- a binary contiguity (adjacency) symetric matrix where each element Cij equals 1 if i-th and j-th spatial units are adjacent, 0 otherwise.

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 vector with Morill segregation index

References

Morill B. (1991) On the measure of geographic segregation. Geography research forum, 11, pp. 25-36.

See Also

Other evenness intragroup indices: Duncan, Wong, Gini, Gorard Intergroup dissimilarity index: DI

Examples

x <- slot(GreHSize, 'data')[ ,3:5]
contiguity <- contig(GreHSize)
foldername <- system.file('extdata', package = 'OasisR')
shapename <- 'GreHSize'

Morill(x, c = contiguity)

Morill(x, spatobj = GreHSize)

Morill(x, folder = foldername, shape = shapename)