benchSAE | R Documentation |
Benchmarked values based on ratio adjustment of the SAE estimates
benchSAE(estim_sae,benchmark_area,area,name_dom,estimator,Nest)
estim_sae |
a data frame containing the arguments |
benchmark_area |
a data frame identifing the area to be benchmarked among with the benchmark value |
area |
character, identified the name of the area to be benchmarked |
name_dom |
character, identified the name of the domains |
estimator |
vector, contain the name of the estimates to be benchmarked |
Nest |
character, identified the name of the total population size for domain |
The benchSAE
function allows (i) to benchmark more than one SAE estimates at times and (ii) to specified the broadarea to be benchmarked, from the national level to a more disaggregated level.
benchSAE
produces a data.frame
with a column of domain indicator and set of columns (as specified in estimator
) of benchmarked point predictions.
Developed by Michele D'Alò
Datta,G. S., Ghosh, M., Steorts, R. and Maples, J. (2010) Bayesian benchmarking with applications to small area estimation. Test, 20, 574–588.
# Load example data data(data_s);data(univ) tot<-aggregate(tot~dom+pro,univ,sum) # One random effect at domain level formula<-as.formula(cbind(emp,unemp,inact)~(1|mun)+ factor(sexage)+factor(edu)+factor(fore)) # Drop from the universe data frame variables not referenced in the formula or in the broadarea univ_1<-univ[,-6] # Estimate mind model benchmarking the unemployment variable example.1<-mind.unit(formula=formula,dom="dom",data=data_s,universe=univ_1,MSE=FALSE) SAEest<-example.1$EBLUP[,c(1,3)] SAEest<-merge(SAEest,tot) SAEest$unemp<-SAEest$unemp/SAEest$tot bench<-data.frame(pro=c(10,11),bb=c(0.27,0.31)) # Benchmark the unemployment point estimates SAEest_bench<-benchSAE(estim_sae=SAEest, benchmark_area=bench, area="pro", name_dom="dom", estimator="unemp", Nest="tot")
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