wilcox_R: What the package does (short line)

ancbootg <-
function(x1,y1,x2,y2,pts,fr1=1,fr2=1,tr=.2,nboot=599){
#
# Compare two independent  groups using the ancova method
# in chapter 9. No assumption is made about the form of the regression
# lines--a running interval smoother is used.
#
#  Assume data are in x1 y1 x2 and y2
#  Comparisons are made at the design points contained in the vector
#  pts
#
m1=elimna(cbind(x1,y1))
x1=m1[,1]
y1=m1[,2]
m1=elimna(cbind(x2,y2))
x2=m1[,1]
y2=m1[,2]
n1<-1
n2<-1
vecn<-1
for(i in 1:length(pts)){
n1[i]<-length(y1[near(x1,pts[i],fr1)])
n2[i]<-length(y2[near(x2,pts[i],fr2)])
}
mat<-matrix(NA,length(pts),8)
dimnames(mat)<-list(NULL,c("X","n1","n2","DIF","TEST","se","ci.low","ci.hi"))
gv<-vector("list",2*length(pts))
for (i in 1:length(pts)){
g1<-y1[near(x1,pts[i],fr1)]
g2<-y2[near(x2,pts[i],fr2)]
g1<-g1[!is.na(g1)]
g2<-g2[!is.na(g2)]
j<-i+length(pts)
gv[[i]]<-g1
gv[[j]]<-g2
}
I1<-diag(length(pts))
I2<-0-I1
con<-rbind(I1,I2)
test<-linconb(gv,con=con,tr=tr,nboot=nboot)
mat[,1]<-pts
mat[,2]<-n1
mat[,3]<-n2
mat[,4]<-test$psihat[,2]
mat[,5]<-test$test[,2]
mat[,6]<-test$test[,3]
mat[,7]<-test$psihat[,3]
mat[,8]<-test$psihat[,4]
list(output=mat,crit=test$crit)
}