superimposing two probability plots with probplot - r

Question

I can create a lognormal probability plot using the probplot() function from the e1071 package. A problem arises when I try to add another set of lognormal data to the first plot. Although I use the command par(new=T), the xaxis of the two plots are different and don't align.
Is there another way to go about this?
I tried using the points() function. However, it appears I need the x and y coordinates to plot it and I don't know how to extract the x, y coordinates from the probplot() function.
''' R
# Program to plot random logn failure times with probability plot
library(e1071)
logn_prob_plot <- function() {
set.seed(1)
x<-rlnorm(10,1,1)
par(bty="l")
par(col.lab="white")
p<-probplot(x,qdist=qlnorm)
par(col.lab="black")
mtext(text="failure time", col="black",side=1,line=3,outer=F)
mtext(text="lognormal probability", col="black",side=2,line=3,outer=F)
set.seed(2)
y=rlnorm(10,2,3)
par(new=T)
par(col.lab="white")
probplot(y,qdist=qlnorm,xlab="fail time",ylab="lognormal probability")
par(col.lab="black")
mtext(text="failure time", col="black",side=1,line=3,outer=F)
mtext(text="lognormal probability", col="black",side=2,line=3,outer=F)
}
logn_prob_plot()
My expected result is two groups of data on the same probability plot with the same x and y axes. Instead, I get two different x-axes that are not aligned.

Answer 1

First lets simulate the variables:
set.seed(1)
x<-rlnorm(10,1,1)
set.seed(2)
y=rlnorm(10,2,3)
The first probplot is:
p<-probplot(x,qdist=qlnorm, meanlog = 1, sdlog = 1)
which produces the output:
The second probplot is:
q <- probplot(y,qdist=qlnorm,meanlog = 2, sdlog = 3)
which produces the output:
Your best shot a merging them is using the scale of the smaller one and discarding some points:
p<-probplot(x,qdist=qlnorm, meanlog = 1, sdlog = 1)
points(sort(x), p[[1]](ppoints(length(x))), col = "red", pch = 19)
lines(q, col = "blue")
points(sort(y), q[[1]](ppoints(length(y))), col = "blue", pch = 19)
which gives:
The red line and points are from the distribution with meanlog = 1, sdlog = 1 and the
blue ones are from the one with meanlog = 2, sdlog = 3.
I further have to warn you that from reading the code of the probplot() function:
xl <- quantile(x, c(0.25, 0.75))
yl <- qdist(c(0.25, 0.75), ...)
slope <- diff(yl)/diff(xl)
the slope of the line is determined only by position the first and the third quartile and not bz what happens elsewhere.