wilcox_R: What the package does (short line)

qhdsm2g <-
function(x1,y1,x2,y2,q=.5,qval=NULL,LP=TRUE,fr=.8,xlab='X',ylab='Y',xout=FALSE,outfun=outpro,...){
#
# Plot of quantile smoother for two groups using qhdsm 
#
# fr controls amount of smoothing
# Missing values are automatically removed.
#
if(!is.null(qval))q=qval
m1<-elimna(cbind(x1,y1))
if(ncol(m1)>3)stop('One covariate only is allowed')
m2<-elimna(cbind(x2,y2))
x1<-m1[,1]
y1<-m1[,2]
x2<-m2[,1]
y2<-m2[,2]
if(xout){
flag<-outfun(m1[,1],plotit=FALSE,...)$keep
m1<-m1[flag,]
x1<-m1[,1]
y1<-m1[,2]
flag<-outfun(m2[,1],plotit=FALSE,...)$keep
m2<-m2[flag,]
x2<-m2[,1]
y2<-m2[,2]
}
flag=order(x1)
x1=x1[flag]
y1=y1[flag]
flag=order(x2)
x2=x2[flag]
y2=y2[flag]
rmd1=NA
rmd2=NA
for(i in 1:length(x1))rmd1[i]<-hd(y1[near(x1,x1[i],fr)],q=q)
for(i in 1:length(x2))rmd2[i]<-hd(y2[near(x2,x2[i],fr)],q=q)
if(LP){
rmd1=lplot(x1,rmd1,plotit=FALSE,pyhat=TRUE,pr=FALSE)$yhat
rmd2=lplot(x2,rmd2,plotit=FALSE,pyhat=TRUE,pr=FALSE)$yhat
}
plot(c(x1,x2),c(y1,y2),type='n',xlab=xlab,ylab=ylab)
points(x1,y1)
points(x2,y2,pch='+')
lines(x1,rmd1)
lines(x2,rmd2,lty=2)
}