survey (version 3.1)

make.calfun: 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

See Also

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))