DIDuncan: A function to compute Duncan dissimilarity segregation index

Description Usage Arguments Value References See Also Examples

View source: R/SegFunctions.R

Description

Duncan's dissimilarity index is the segregation index most commonly used in the literature. It is derived from Lorenz curves as the maximum difference between the segregation curve and the diagonal. The index measures the unevenness of a group's spatial distribution compared to another group. It can be interpreted as the share of the group that would have to move to achieve an even distribution compared to another group.

Usage

1

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.

Value

a matrix containing dissimilarity index values

References

Duncan O. D. and Duncan B. (1955) A Methodological Analysis of Segregation Indexes. American Sociological Review 41, pp. 210-217

See Also

Other one-group evenness indices: ISDuncan, Gini, Gorard, Atkinson, HTheil, ISWong, ISMorrill, ISMorrillK

Between groups dissimilarity indices: DIMorrill, DIMorrillK, DIWong

Examples

1
2
x <- segdata@data[ ,1:2]
DIDuncan(x) 

Example output

     [,1] [,2]
[1,]    0    1
[2,]    1    0

OasisR documentation built on July 2, 2020, 3:14 a.m.

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