This package provides various indices, like Crude Migration Rate, different Gini indices or the Coefficient of Variation among others, to show the (un)equality of migration.
Most recent stable version can be installed directly from CRAN:
install.packages('migration.indices')
Or please use devtools
for the development version:
library(devtools)
install_github('migration.indices', 'daroczig')
The below migration matrix is a demo dataset based on
library(migration.indices)
data(migration.hyp)
<- migration.gini(migration.hyp)
res res
Resulting in:
Total Flows Gini Index: 0.2222222
Rows Gini Index: 0
Standardized Rows Gini Index: 0
Columns Gini Index: 0.05555556
Standardized Columns Gini Index: 25
Exchange Gini Index: 0.05555556
Standardized Exchange Gini Index: 25
In-migration Field Gini Index: vector
Weighted In-migration Gini Index: 0.1222222
Out-migration Field Gini Index: vector
Weighted Out-migration Gini Index: 0
Migration-weighted Mean Gini Index: 0.06111111
Where In and Out-migration Field Gini Index are vectors:
> res$migration.gini.in
[1] 0.2000000 0.5000000 0.3333333
> res$migration.gini.out
[1] 0 0 0
Using the Global Bilateral Migration Database (2000) of World Bank:
data(migration.world)
migration.gini(migration.world)
Results in:
Total Flows Gini Index: 0.9855174
Rows Gini Index: 0.004272225
Standardized Rows Gini Index: 0.4335008
Columns Gini Index: 0.004067787
Standardized Columns Gini Index: 0.4127565
Exchange Gini Index: 1.382263e-05
Standardized Exchange Gini Index: 0.001402575
In-migration Field Gini Index: vector
Weighted In-migration Gini Index: 0.004241788
Out-migration Field Gini Index: vector
Weighted Out-migration Gini Index: 0.004171575
Migration-weighted Mean Gini Index: 0.004206681