Description Usage Arguments Value References See Also Examples
Estimate the Gini coefficient, which is a measure for inequality, and its linearization.
1 2 3 4 5 6 7 8 9 10 11 |
Y |
Study variable (for example equalized disposable income). One dimensional object convertible to one-column |
id |
Optional variable for unit ID codes. One dimensional object convertible to one-column |
weight |
Optional weight variable. One dimensional object convertible to one-column |
sort |
Optional variable to be used as tie-breaker for sorting. One dimensional object convertible to one-column |
Dom |
Optional variables used to define population domains. If supplied, linearization of the Gini is done for each domain. An object convertible to |
period |
Optional variable for survey period. If supplied, linearization of the Gini is done for each time period. Object convertible to |
dataset |
Optional survey data object convertible to |
var_name |
A character specifying the name of the linearized variable. |
checking |
Optional variable if this variable is TRUE, then function checks data preparation errors, otherwise not checked. This variable by default is TRUE. |
A list with two objects are returned by the function:
value
- a data.table
containing the estimated Gini coefficients (in percentage) by Langel and Tille (2012) and Eurostat.
lin
- a data.table
containing the linearized variables of the Gini coefficients (in percentage) by Langel and Tille (2012).
Eric Graf, Yves Tille, Variance Estimation Using Linearization for Poverty and Social Exclusion Indicators, Survey Methodology, June 2014 61 Vol. 40, No. 1, pp. 61-79, Statistics Canada, Catalogue no. 12-001-X, URL https://www150.statcan.gc.ca/n1/pub/12-001-x/12-001-x2014001-eng.pdf
Jean-Claude Deville (1999). Variance estimation for complex statistics and estimators: linearization and residual techniques. Survey Methodology, 25, 193-203, URL https://www150.statcan.gc.ca/n1/pub/12-001-x/1999002/article/4882-eng.pdf.
Matti Langel, Yves Tille, Corrado Gini, a pioneer in balanced sampling and inequality theory. Metron - International Journal of Statistics, 2011, vol. LXIX, n. 1, pp. 45-65, URL http://dx.doi.org/10.1007/BF03263549.
Working group on Statistics on Income and Living Conditions (2004) Common cross-sectional EU indicators based on EU-SILC; the gender pay gap. EU-SILC 131-rev/04, Eurostat.
lingini
,
linqsr
,
varpoord
,
vardcrospoor
,
vardchangespoor
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | library("data.table")
library("laeken")
data("eusilc")
dataset1 <- data.table(IDd = paste0("V", 1 : nrow(eusilc)), eusilc)
# Full population
dat1 <- lingini2(Y = "eqIncome", id = "IDd",
weight = "rb050", dataset = dataset1)
dat1$value
## Not run:
# By domains
dat2 <- lingini2(Y = "eqIncome", id = "IDd",
weight = "rb050", Dom = c("db040"),
dataset = dataset1)
dat2$value
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.