R/qregsm.R

In musto101/wilcox_R: What the package does (short line)

qregsm <-
function(x, y,est=hd,qval=.5,sm=TRUE,plotit=TRUE,pyhat=FALSE,fr=0.8,nboot=40,xlab="X",
ylab="Y")
{
#
# Do a smooth of x versus the quantiles of y
#
# qval indicates quantiles of interest.
# Example: qval=c(.2,.8) will create two smooths, one for the
# .2 quantile and the other for the .8 quantile.
#
# est can be any quantile estimator having the argument qval, indicating
# the quantile to be used.
#
# est = hd uses Harrel Davis estimator,
# est = qest uses a single order statistic.
#
# sm=T, bagging will be used.
# pyhat=T returns the estimates
#
x<-as.matrix(x)
X<-cbind(x,y)
X<-elimna(X)
np<-ncol(X)
p<-np-1
x<-X[,1:p]
x<-as.matrix(x)
y<-X[,np]
vals<-matrix(NA,ncol=length(y),nrow=length(qval))
for(i in 1:length(qval)){
if(sm)vals[i,]<-rplotsm(x,y,est=est,q=qval[i],pyhat=TRUE,plotit=FALSE,fr=fr,nboot=nboot)$yhat
if(!sm)vals[i,]<-rungen(x,y,est=est,q=qval[i],pyhat=TRUE,plotit=FALSE,fr=fr)$output
}
if(p==1){
if(plotit){
plot(x,y,xlab=xlab,ylab=ylab)
for(i in 1:length(qval)){
sx <- sort(x)
xorder <- order(x)
sysm <- vals[i,]
#lines(sx, sysm)
lines(sx, sysm[xorder])
}}}
output <- "Done"
if(pyhat)output <- vals
output
}