make.calfun {survey} R Documentation

## Calibration metrics

### Description

Create calibration metric for use in `calibrate`. The function `F` is the link function described in section 2 of Deville et al. To create a new calibration metric, specify F-1 and its derivative. The package provides `cal.linear`, `cal.raking`, and `cal.logit`.

### Usage

```make.calfun(Fm1, dF, name)
```

### Arguments

 `Fm1` Function F-1 taking a vector `u` and a vector of length 2, `bounds`. `dF` Derivative of `Fm1` wrt `u`: arguments `u` and `bounds` `name` Character string to use as name

### Value

An object of class `"calfun"`

### References

Deville J-C, Sarndal C-E, Sautory O (1993) Generalized Raking Procedures in Survey Sampling. JASA 88:1013-1020

Deville J-C, Sarndal C-E (1992) Calibration Estimators in Survey Sampling. JASA 87: 376-382

`calibrate`

### Examples

```str(cal.linear)
cal.linear\$Fm1
cal.linear\$dF

hellinger <- make.calfun(Fm1=function(u, bounds)  ((1-u/2)^-2)-1,
dF= function(u, bounds) (1-u/2)^-3 ,
name="hellinger distance")

hellinger

data(api)
dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc)

svymean(~api00,calibrate(dclus1, ~api99, pop=c(6194, 3914069),
calfun=hellinger))

svymean(~api00,calibrate(dclus1, ~api99, pop=c(6194, 3914069),
calfun=cal.linear))

svymean(~api00,calibrate(dclus1, ~api99, pop=c(6194,3914069),
calfun=cal.raking))
```

[Package survey version 3.18 Index]