Provides user-friendly tools for calibration in survey sampling. The package is production-oriented, and its interface is inspired by the famous popular macro 'Calmar' for SAS, so that 'Calmar' users can quickly get used to 'icarus'. In addition to calibration (with linear, raking and logit methods), 'icarus' features functions for calibration on tight bounds and penalized calibration.
Icarus (Icarus Calibrates And Reweights Units in Samples) is an R package providing useful functions for calibration and reweighting estimators in survey sampling. The former name of this package was gaston.
To cite Icarus in publications use: Rebecq, Antoine (2016). Icarus: an R package for calibration in survey sampling. R package version 0.2.0.
You can use the following instruction to install icarus (from CRAN):
However, if you wish to install the latest version of icarus, you can use devtools and install directly from this github repo:
In this example, we perform calibration (with the "raking" method) on the test dataset data_ex2 included in icarus:
library(icarus)N <- 300 ## Population size## Compute the Horvitz-Thompson estimator (returns 1.666667)weightedMean(data_ex2$cinema, data_ex2$poids, N)## Add calibration marginsmar1 <- c("categ",3,80,90,60)mar2 <- c("sexe",2,140,90,0)mar3 <- c("service",2,100,130,0)mar4 <- c("salaire", 0, 470000,0,0)margins <- rbind(mar1, mar2, mar3, mar4)## Compute calibration weightswCal <- calibration(data=data_ex2, marginMatrix=margins, colWeights="poids", method="raking", description=FALSE)## Value of the calibrated estimator: 2.471917weightedMean(data_ex2$cinema, wCal, N)