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I am building an R package to display Weibull plots (using graphics::plot ) in R. The plot has a log-transformed x -axis and a Weibull-transformed y -axis (for lack of a better description). The two-parameter Weibull distribution can thus be represented as a straight line on this plot. The logarithmic transformation of the x -axis is as simple as adding the log="x" parameter to plot() or curve() . How can I supply the y -axis transformation in an elegant way, so that all graphics-related plotting will work on my axis-transformed plot? To demonstrate what I need, run the following example code: ## initialisation ## beta <- 2;eta <- 1000 ticks <- c(seq(0.01,0.09,0.01),(1:9)/10,seq(0.91,0.99,0.01)) F0inv <- function (p) log(qweibull(p, 1, 1)) # this is the transformation function F0 <- function (q) exp(-exp(q)) # this is the inverse of the transformation function weibull <- function(x)pweibull(x,beta,eta) # the curve of this function represents the weibull distribution # as a straight line on weibull paper weibull2 <- function(x)F0inv(weibull(x)) First an example of a Weibull distribution with beta=2 and eta=1000 on a regular, untransformed plot: ## untransformed axes ## curve(weibull ,xlim=c(100,1e4),ylim=c(0.01,0.99)) abline(h=ticks,col="lightgray") This plot is useless for Weibull analysis. Here is my currently implemented solution that transforms the data with function F0inv() and modifies the y -axis of the plot. Notice that I have to use F0inv() on all y -axis related data. ## transformed axis with F0inv() ## curve(weibull2,xlim=c(100,1e4),ylim=F0inv(c(0.01,0.99)),log="x",axes=

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