R/ees.ci.R

In musto101/wilcox_R: What the package does (short line)

ees.ci <-
function(x,y,SEED=TRUE,nboot=400,tr=.2,alpha=.05,pr=TRUE){
#
# Compute a 1-alpha  confidence interval
# for a robust, heteroscedastic  measure of effect size
#
if(SEED)set.seed(2) # set seed of random number generator so that
#             results can be duplicated.
x=elimna(x)
y=elimna(y)
bvec=0
datax<-matrix(sample(x,size=length(x)*nboot,replace=TRUE),nrow=nboot)
datay<-matrix(sample(y,size=length(x)*nboot,replace=TRUE),nrow=nboot)
for(i in 1:nboot){
bvec[i]=yuenv2(datax[i,],datay[i,],tr=tr,SEED=FALSE)$Var.Explained
}
bvec<-sort(bvec)
crit<-alpha/2
icl<-round(crit*nboot)+1
icu<-nboot-icl
ci<-NA
ci[1]<-bvec[icl]
pchk=yuen(x,y,tr=tr)$p.value
if(pchk>alpha)ci[1]=0
ci[2]<-bvec[icu]
if(ci[1]<0)ci[1]=0
ci=sqrt(ci)
ci
}