wilcox_R: What the package does (short line)

Qancsm <-
function(x1,y1,x2,y2,crit.mat=NULL,nboot=200,SEED=TRUE,REP.CRIT=FALSE,
qval=.5,q=NULL,xlab="X",ylab="Y",plotit=TRUE,pr=TRUE,xout=FALSE,outfun=out,...){
#
# Compare two nonparametric
# regression lines corresponding to two independent groups
#  using the depths of smooths.
#
# NULL hypothesis: regression lines are identical in terms of the median
# of Y, given$X, for all X
# The method is based on comparing the depth of the fitted regression lines
# and is essentially a slight variation of the method in Wilcox
# (in press) Journal of Data Science.
#
# One covariate only is allowed.
#
if(ncol(as.matrix(x1))>1)stop("One covariate only is allowed")
if(!is.null(q))qval=q
if(xout){
flag1=outfun(x1)$keep
flag2=outfun(x2)$keep
x1=x1[flag1]
y1=y1[flag1]
x2=x2[flag2]
y2=y2[flag2]
}
if(SEED)set.seed(2)
xy=elimna(cbind(x1,y1))
x1=xy[,1]
xord=order(x1)
x1=x1[xord]
y1=xy[xord,2]
xy=elimna(cbind(x2,y2))
x2=xy[,1]
xord=order(x2)
x2=x2[xord]
y2=xy[xord,2]
n1=length(y1)
n2=length(y2)
if(is.null(crit.mat[1])){
if(pr)print("Determining critical value. This might take a while")
crit.val=NA
yall=c(y1,y2)
xall=c(x1,x2)
nn=n1+n2
il=n1+1
for(i in 1:nboot){
data=sample(nn,nn,T)
yy1=yall[data[1:n1]]
yy2=yall[data[il:nn]]
xx1=xall[data[1:n1]]
xx2=xall[data[il:nn]]
crit.mat[i]=Qdepthcom(xx1,yy1,xx2,yy2,qval=qval)
}}
dep=Qdepthcom(x1,y1,x2,y2,qval=qval)
pv=1-mean(crit.mat<dep)
if(!REP.CRIT)crit.mat=NULL
if(plotit){
plot(c(x1,x2),c(y1,y2),type="n",xlab=xlab,ylab=ylab)
temp1=cobs(x1,y1,print.mesg=FALSE,print.warn=FALSE,tau=qval)
temp2=cobs(x2,y2,print.mesg=FALSE,print.warn=FALSE,tau=qval)
points(x1,y1)
points(x2,y2,pch="+")
lines(x1,temp1$fitted)
lines(x2,temp2$fitted,lty=2)
}
list(p.value=pv,crit.mat=crit.mat,test.depth=dep)
}