Utility functions for indicators on social exclusion and poverty
Test for class, print and take subsets of indicators on social exclusion and poverty.
is.indicator(x) is.arpr(x) is.qsr(x) is.rmpg(x) is.gini(x) is.prop(x) is.gpg(x) ## S3 method for class 'indicator' print(x, ...) ## S3 method for class 'arpr' print(x, ...) ## S3 method for class 'rmpg' print(x, ...) ## S3 method for class 'indicator' subset(x, years = NULL, strata = NULL, ...) ## S3 method for class 'arpr' subset(x, years = NULL, strata = NULL, ...) ## S3 method for class 'rmpg' subset(x, years = NULL, strata = NULL, ...)
x |
for |
... |
additional arguments to be passed to and from methods. |
years |
an optional numeric vector giving the years to be extracted. |
strata |
an optional vector giving the domains of the breakdown to be extracted. |
is.indicator returns TRUE if x inherits from
class "indicator" and FALSE otherwise.
is.arpr returns TRUE if x inherits from class
"arpr" and FALSE otherwise.
is.qsr returns TRUE if x inherits from class
"qsr" and FALSE otherwise.
is.rmpg returns TRUE if x inherits from class
"rmpg" and FALSE otherwise.
is.gini returns TRUE if x inherits from class
"gini" and FALSE otherwise.
is.gini returns TRUE if x inherits from class
"gini" and FALSE otherwise.
print.indicator, print.arpr and print.rmpg return
x invisibly.
subset.indicator, subset.arpr and subset.rmpg return a
subset of x of the same class.
A. Alfons and M. Templ (2013) Estimation of Social Exclusion Indicators from Complex Surveys: The R Package laeken. Journal of Statistical Software, 54(15), 1–25. URL http://www.jstatsoft.org/v54/i15/
data(eusilc)
# at-risk-of-poverty rate
a <- arpr("eqIncome", weights = "rb050",
breakdown = "db040", data = eusilc)
print(a)
is.arpr(a)
is.indicator(a)
subset(a, strata = c("Lower Austria", "Vienna"))
# quintile share ratio
q <- qsr("eqIncome", weights = "rb050",
breakdown = "db040", data = eusilc)
print(q)
is.qsr(q)
is.indicator(q)
subset(q, strata = c("Lower Austria", "Vienna"))
# relative median at-risk-of-poverty gap
r <- rmpg("eqIncome", weights = "rb050",
breakdown = "db040", data = eusilc)
print(r)
is.rmpg(r)
is.indicator(r)
subset(r, strata = c("Lower Austria", "Vienna"))
# Gini coefficient
g <- gini("eqIncome", weights = "rb050",
breakdown = "db040", data = eusilc)
print(g)
is.gini(g)
is.indicator(g)
subset(g, strata = c("Lower Austria", "Vienna"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.