This is the development place for the R-package `surveysd`

. The package can be used to estimate the standard deviation of estimates in complex surveys using bootstrap weights.

```
# Install release version from CRAN
install.packages("surveysd")
# Install development version from GitHub
devtools::install_github("statistikat/surveysd")
```

Bootstrapping has long been around and used widely to estimate confidence intervals and standard errors of point estimates. This package aims to combine all necessary steps for applying a calibrated bootstrapping procedure with custom estimating functions.

A typical workflow with this package consists of three steps. To see these concepts in practice, please refer to the getting started vignette.

- Calibrated weights can be generated with the function
`ipf()`

using an iterative proportional updating algorithm. - Bootstrap samples are drawn with rescaled bootstrapping in the function
`draw.bootstrap()`

. - These samples can then be calibrated with an iterative proportional updating algorithm using
`recalib()`

. - Finally, estimation functions can be applied over all bootstrap replicates with
`calc.stError()`

.

More information can be found on the github-pages site for surveysd.

- The methodology is covered in the methodology vignette.
- A more comprehensive documentation of
`calc.stError()`

is available in the error estimation vignette.