wilcox_R: What the package does (short line)

rdplot <-
function(x,fr=NA,plotit=TRUE,theta=50,phi=25,expand=.5,pyhat=FALSE,pts=NA,
xlab="X",ylab="",ticktype="simple"){
#
# Expected frequency curve
#
# fr controls amount of smoothing
#  theta is the azimuthal direction and phi the colatitude
#
plotit<-as.logical(plotit)
x<-elimna(x)
x<-as.matrix(x)
rmd<-NA
if(ncol(x)==1){
if(is.na(fr))fr<-.8
if(is.na(pts[1]))pts<-x
for(i in 1:length(pts)){
rmd[i]<-sum(near(x,pts[i],fr))
}
if(mad(x)!=0)rmd<-rmd/(2*fr*mad(x))
rmd<-rmd/length(x)
if(plotit){
plot(pts,rmd,type="n",ylab=ylab,xlab=xlab)
sx<-sort(pts)
xorder<-order(pts)
sysm<-rmd[xorder]
lines(sx,sysm)
}}
if(ncol(x)>1){
library(MASS)
if(is.na(fr))fr<-.6
m<-cov.mve(x)
for(i in 1:nrow(x)){
rmd[i]<-sum(near3d(x,x[i,],fr,m))
}
rmd<-rmd/nrow(x)
if(plotit && ncol(x)==2){
library(akima)
fitr<-rmd
iout<-c(1:length(fitr))
nm1<-length(fitr)-1
for(i in 1:nm1){
ip1<-i+1
for(k in ip1:length(fitr))if(sum(x[i,]==x[k,])==2)iout[k]<-0
}
fitr<-fitr[iout>=1]
mkeep<-x[iout>=1,]
fit<-interp(mkeep[,1],mkeep[,2],fitr)
persp(fit,theta=theta,phi=phi,expand=expand,xlab="Var 1",ylab="Var 2",zlab="",
ticktype=ticktype)
}
}
if(pyhat)last<-rmd
if(!pyhat)last<-"Done"
last
}