wilcox_R: What the package does (short line)

qcomhd <-
function(x,y,q=c(.1,.25,.5,.75,.9),nboot=2000,plotit=TRUE,SEED=TRUE,xlab="Group 1",ylab="Est.1-Est.2",alpha=.05){
#
# Compare quantiles using pb2gen
# via hd estimator. Tied values are allowed.
# When comparing lower or upper quartiles, both power and the probability of Type I error
# compare well to other methods that have been derived.
# q: can be used to specify the quantiles to be compared
# q defaults to comparing the .1,.25,.5,.75, and .9 quantiles
#   Function returns p-values and critical p-values based on Hochberg's method.
#
if(SEED)set.seed(2)
pv=NULL
output=matrix(NA,nrow=length(q),ncol=10)
dimnames(output)<-list(NULL,c("q","n1","n2","est.1","est.2","est.1_minus_est.2","ci.low","ci.up","p_crit","p-value"))
for(i in 1:length(q)){
output[i,1]=q[i]
output[i,2]=length(elimna(x))
output[i,3]=length(elimna(y))
output[i,4]=hd(x,q=q[i])
output[i,5]=hd(y,q=q[i])
output[i,6]=output[i,4]-output[i,5]
temp=pb2gen(x,y,nboot=nboot,est=hd,q=q[i],SEED=FALSE,alpha=alpha,pr=FALSE)
output[i,7]=temp$ci[1]
output[i,8]=temp$ci[2]
output[i,10]=temp$p.value
}
temp=order(output[,10],decreasing=TRUE)
zvec=alpha/c(1:length(q))
output[temp,9]=zvec
#print(output)
output <- data.frame(output)
output$signif=rep("YES",nrow(output))
for(i in 1:nrow(output)){
if(output[temp[i],10]>output[temp[i],9])output$signif[temp[i]]="NO"
if(output[temp[i],10]<=output[temp[i],9])break
}
if(plotit){
xax=rep(output[,4],3)
yax=c(output[,6],output[,7],output[,8])
plot(xax,yax,xlab=xlab,ylab=ylab,type="n")
points(output[,4],output[,6],pch="*")
lines(output[,4],output[,6])
points(output[,4],output[,7],pch="+")
points(output[,4],output[,8],pch="+")
}
output
}