| variance {laeken} | R Documentation |
Variance and confidence intervals of indicators on social exclusion and poverty
Description
Compute variance and confidence interval estimates of indicators on social exclusion and poverty.
Usage
variance(
inc,
weights = NULL,
years = NULL,
breakdown = NULL,
design = NULL,
cluster = NULL,
data = NULL,
indicator,
alpha = 0.05,
na.rm = FALSE,
type = "bootstrap",
gender = NULL,
method = NULL,
...
)
Arguments
inc |
either a numeric vector giving the equivalized disposable income,
or (if |
weights |
optional; either a numeric vector giving the personal sample
weights, or (if |
years |
optional; either a numeric vector giving the different years of
the survey, or (if |
breakdown |
optional; either a numeric vector giving different domains,
or (if |
design |
optional; either an integer vector or factor giving different
strata for stratified sampling designs, or (if |
cluster |
optional; either an integer vector or factor giving different
clusters for cluster sampling designs, or (if |
data |
an optional |
indicator |
an object inheriting from the class |
alpha |
a numeric value giving the significance level to be used for
computing the confidence interval(s) (i.e., the confidence level is |
na.rm |
a logical indicating whether missing values should be removed. |
type |
a character string specifying the type of variance estimation to
be used. Currently, only |
gender |
either a numeric vector giving the gender, or (if |
method |
a character string specifying the method to be used (only for
|
... |
additional arguments to be passed to |
Details
This is a wrapper function for computing variance and confidence interval estimates of indicators on social exclusion and poverty.
Value
An object of the same class as indicator is returned. See
arpr, qsr, rmpg or
gini for details on the components.
Author(s)
Andreas Alfons
References
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. doi:10.18637/jss.v054.i15
See Also
bootVar, arpr, qsr,
rmpg, gini
Examples
data(eusilc)
a <- arpr("eqIncome", weights = "rb050", data = eusilc)
## naive bootstrap
variance("eqIncome", weights = "rb050", design = "db040",
data = eusilc, indicator = a, R = 50,
bootType = "naive", seed = 123)
## bootstrap with calibration
variance("eqIncome", weights = "rb050", design = "db040",
data = eusilc, indicator = a, R = 50,
X = calibVars(eusilc$db040), seed = 123)