Nothing
plotrsr <-
function(n=20:50, q=c(90,95), ...){
# n: sequence of series size
# q: vector of quantile values
# ... : argument for function lines()
probs<-TPout$probs
quant<-probs*100
nn<-TPout$n # seq(6,70,2) : the original sequence of n that was run for RSR
if(any(!(q%in%quant)))stop("One of the quantiles is out of bound. Type 'TPout$probs*100'
to see possible quantile values.")
MV=TPout$MeanVar
m<-length(quant)
w<-quant%in%q
ind<-(1:m)[w]
LM=~I(1/nn)+I(1/nn^2)
Qts=paste(c("Qt"),probs[ind]*100,sep="")
Wt=paste(c("1/Var"),probs[ind]*100,sep="")
Regressor=paste(as.character(LM),sep="")
Regressor=sapply(Qts, function(a) paste(a,"~", Regressor[2], sep=""))
AllMod=function(X){
apply(cbind(Regressor, Wt),1, function(Regressor){
V=eval(parse(text=Regressor[2]),X, parent.frame())
do.call("lm", list(as.formula(Regressor[1]), weights=quote(V), data=quote(X)))})
}
Res=lapply(MV, AllMod)[[1]]
pred.val<-sapply(Res, function(x,n) predict(x, data.frame(nn=n)),n)
y.min=min(pred.val)
y.max=max(pred.val)
plot(c(min(n),max(n)),c(y.min,y.max),type="n",xlab="n",ylab="Quantiles")
for( i in 1:length(ind)){
lines(n, pred.val[,i],...)
text(min(n) ,pred.val[1,i], label=names(as.data.frame(pred.val))[i], cex=0.8)
}
}
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