bootVar(inc, weights = NULL, years = NULL,
breakdown = NULL, design = NULL, data = NULL,
indicator, R = 100, bootType = c("calibrate", "naive"),
X, totals = NULL, ciType = c("perc", "norm", "basic"),
alpha = 0.05, seed = NULL, na.rm = FALSE,
gender = NULL, method = "mean", ...)data is not NULL)
a character string, an integer or a logical vector
specifying the corresponding column of data.data is not
NULL) a character string, an integer or a logical
vector specifying the corresponding column of
data.data is not
NULL) a character string, an integer or a logical
vector specifying the corresponding column of
data. If supdata is not NULL)
a character string, an integer or a logical vector
specifying the corresponding column of data. If
supplied, the valuesdata is not NULL) a
character string, an integer or a logical vector
specifying the corresponding column of data.frame."calibrate" (for calibration of the sample weights
of the resampled observations in every iteration) and
"naive" (for a naive bobootType is "calibrate", a
matrix of calibration variables.bootType is
"calibrate", this gives the population totals. If
years is NULL, a vector should be supplied,
otherwise a matrix in which each row contains the
population totals of t"perc", "norm" and "basic" (see
boot.ci).alpha),
or NULL.data is not NULL) a character
string, an integer or a logical vector specifying the
corresponding column of data.bootType is "calibrate",
additional arguments to be passed to
calibWeights.variance, calibWeights,
arpr, qsr,
rmpg, ginidata(eusilc)
a <- arpr("eqIncome", weights = "rb050", data = eusilc)
## naive bootstrap
bootVar("eqIncome", weights = "rb050", design = "db040",
data = eusilc, indicator = a, bootType = "naive", seed = 123)
## bootstrap with calibration
bootVar("eqIncome", weights = "rb050", design = "db040",
data = eusilc, indicator = a, X = calibVars(eusilc$db040),
seed = 123)Run the code above in your browser using DataLab