laeken: bootVar – R documentation

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bootVar

Bootstrap 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 based on bootstrap resampling.

Usage

bootVar(inc, weights = NULL, years = NULL, breakdown = NULL,
  design = NULL, cluster = 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 = NULL, ...)

Arguments

`inc`	either a numeric vector giving the equivalized disposable income, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`.
`weights`	optional; either a numeric vector giving the personal sample weights, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`.
`years`	optional; either a numeric vector giving the different years of the survey, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`. If supplied, values are computed for each year.
`breakdown`	optional; either a numeric vector giving different domains, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`. If supplied, the values for each domain are computed in addition to the overall value.
`design`	optional; either an integer vector or factor giving different strata for stratified sampling designs, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`. If supplied, this is used as `strata` argument in the call to `boot`.
`cluster`	optional; either an integer vector or factor giving different clusters for cluster sampling designs, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`.
`data`	an optional `data.frame`.
`indicator`	an object inheriting from the class `"indicator"` that contains the point estimates of the indicator (see `arpr`, `qsr`, `rmpg` or `gini`).
`R`	a numeric value giving the number of bootstrap replicates.
`bootType`	a character string specifying the type of bootstap to be performed. Possible values are `"calibrate"` (for calibration of the sample weights of the resampled observations in every iteration) and `"naive"` (for a naive bootstrap without calibration of the sample weights).
`X`	if `bootType` is `"calibrate"`, a matrix of calibration variables.
`totals`	numeric; if `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 the respective year. If this is `NULL` (the default), the population totals are computed from the sample weights using the Horvitz-Thompson estimator.
`ciType`	a character string specifying the type of confidence interval(s) to be computed. Possible values are `"perc"`, `"norm"` and `"basic"` (see `boot.ci`).
`alpha`	a numeric value giving the significance level to be used for computing the confidence interval(s) (i.e., the confidence level is 1 - `alpha`), or `NULL`.
`seed`	optional; an integer value to be used as the seed of the random number generator, or an integer vector containing the state of the random number generator to be restored.
`na.rm`	a logical indicating whether missing values should be removed.
`gender`	either a numeric vector giving the gender, or (if `data` is not `NULL`) a character string, an integer or a logical vector specifying the corresponding column of `data`.
`method`	a character string specifying the method to be used (only for `gpg`). Possible values are `"mean"` for the mean, and `"median"` for the median. If weights are provided, the weighted mean or weighted median is estimated.
`...`	if `bootType` is `"calibrate"`, additional arguments to be passed to `calibWeights`.

Value

An object of the same class as indicator is returned. See arpr, qsr, rmpg or gini for details on the components.

Note

This function gives reasonable variance estimates for basic sample designs such as simple random sampling or stratified simple random sampling.

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. URL http://www.jstatsoft.org/v54/i15/

Examples

data(eusilc)
a <- arpr("eqIncome", weights = "rb050", data = eusilc)

## naive bootstrap
bootVar("eqIncome", weights = "rb050", design = "db040",
    data = eusilc, indicator = a, R = 50,
    bootType = "naive", seed = 123)

## bootstrap with calibration
bootVar("eqIncome", weights = "rb050", design = "db040",
    data = eusilc, indicator = a, R = 50,
    X = calibVars(eusilc$db040), seed = 123)

laeken

Estimation of Indicators on Social Exclusion and Poverty

v0.5.1

GPL (>= 2)

Authors

Andreas Alfons [aut, cre], Josef Holzer [aut], Matthias Templ [aut], Alexander Haider [ctb]

Initial release

2020-02-05