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`

.

1 | ```
make.calfun(Fm1, dF, name)
``` |

`Fm1` |
Function |

`dF` |
Derivative of |

`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

`calibrate`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
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))
``` |

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