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 data is not NULL) a character string, an integer or a
logical vector specifying the corresponding column of data. If
supplied, the valdata is not
NULL) a character string, an integer or a logical vector specifying
the corresponding column data.frame."calibrate" (for calibration of the
sample weights of the resampled observations in every iteration) and
"naive" (for a naivebootType 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 o"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