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, cal.logit, which are standard, and cal.sinh from the CALMAR2 macro, for which F is the derivative of the inverse hyperbolic sine.

### 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 4.1-1 Index]