make.calfun {survey} | R Documentation |
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
.
make.calfun(Fm1, dF, name)
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 |
An object of class "calfun"
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
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))