simFrame (version 0.5.0)

SampleControl-class: Class "SampleControl"

Description

Class for controlling the setup of samples.

Objects from the Class

Objects can be created by calls of the form new("SampleControl", ...) or SampleControl(...).

Details

There are some restrictions on the argument names of the function supplied to fun. If it needs population data as input, the corresponding argument should be called x and should expect a data.frame. If the sampling method only needs the population size as input, the argument should be called N. Note that fun is not expected to have both x and N as arguments, and that the latter is much faster for stratified sampling or group sampling. Furthermore, if the function has arguments for sample size and probability weights, they should be called size and prob, respectively. Note that a function with prob as its only argument is perfectly valid (for probability proportional to size sampling). Further arguments of fun may be supplied as a list via the slot dots.

Extends

Class "VirtualSampleControl", directly. Class "OptSampleControl", by class "VirtualSampleControl", distance 2.

UML class diagram

A slightly simplified UML class diagram of the framework can be found in Figure 1 of the package vignette An Object-Oriented Framework for Statistical Simulation: The RPackage simFrame. Use vignette("simFrame-intro") to view this vignette.

References

Alfons, A., Templ, M. and Filzmoser, P. (2010) An Object-Oriented Framework for Statistical Simulation: The RPackage simFrame. Journal of Statistical Software, 37(3), 1--36. URL http://www.jstatsoft.org/v37/i03/.

See Also

"VirtualSampleControl", "TwoStageControl", "SampleSetup", setup, draw

Examples

data(eusilcP)

## simple random sampling
srsc <- SampleControl(size = 20)
draw(eusilcP[, c("id", "eqIncome")], srsc)

## group sampling
gsc <- SampleControl(grouping = "hid", size = 10)
draw(eusilcP[, c("hid", "hid", "eqIncome")], gsc)

## stratified simple random sampling
ssrsc <- SampleControl(design = "region", 
    size = c(2, 5, 5, 3, 4, 5, 3, 5, 2))
draw(eusilcP[, c("id", "region", "eqIncome")], ssrsc)

## stratified group sampling
sgsc <- SampleControl(design = "region", grouping = "hid", 
    size = c(2, 5, 5, 3, 4, 5, 3, 5, 2))
draw(eusilcP[, c("hid", "id", "region", "eqIncome")], sgsc)