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Does anyone know how to create log probability plot like this one in R where the x-axis is probability and y-axis is in log-scale. I read and downloaded the package heR.Misc package but I don't know how to use it. !enter image description here

Amateur
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    Have a look on [this](http://stats.stackexchange.com/q/27607/3903) – MYaseen208 Jun 28 '12 at 03:26
  • That plot's x-axis was not labeled with probabilities but with sample values. I'm thinking you want the "transpose" of such a graph. – IRTFM Jun 28 '12 at 12:18
  • @ DWin: What do you mean by transpose that graph? That graph is not quite ideal yet but it's ok. Ideally we would like a graph like the one I posted with gridlines and probability from 0.01 to 99.99% – Amateur Jun 28 '12 at 19:37

2 Answers2

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#create log probablity plot
#MPM 131201
#Make some dummy data
set.seed(21)
Dt<-as.data.frame(rlnorm(625, log(10), log(2.5)))
names(Dt)<-"Au_ppm"

#Create probablity scale lines and associated labels - 
PrbGrd <- qnorm(c(0.001,0.01, 0.05, 0.10,0.20,0.30,0.40, 0.50, 0.60, 0.70,0.80,0.90,0.95,0.99,0.999))
PrbGrdL<-c("0.1","1","5","10","20","30","40","50","60","70","80","90","95","99","99.9")

#create some value grid lines then convert to logs
ValGrd<-c(seq(0.001,0.01,0.001),seq(0.01,0.1,0.01),seq(0.1,1,0.1),seq(1,10,1),seq(10,100,10))
ValGrd<-log10(ValGrd)

#load up lattice packages - latticeExtra for nice log scale
require(lattice)
require(latticeExtra)

#Use qqmath to make the plot (note lattice does not work for weighted data - shame about that)

qqmath(~ Au_ppm, 
        data= Dt,
            distribution = function(p) qnorm(p),
        main = "Normal probablity / log (base 10) plot",
        pch=20,
        cex=0.5,
        xlab="Normal distribution scale (%)",
        scales=list(y=list(log=10,alternating=1),x = list(at = PrbGrd, labels = PrbGrdL, cex = 0.8)),
        yscale.components=yscale.components.log10ticks,
        panel=function(x,...){
            panel.abline(v=PrbGrd ,col="grey",lty=3)
            panel.abline(h=ValGrd,col="grey",lty=3)
            panel.qqmath(x,distribution=qnorm)
        }

    )
Markm0705
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1

Here is an example using base R, simplified a bit from this post: (https://stat.ethz.ch/pipermail/r-help/2004-February/045370.html). 

## Make some data
y <- rnorm(n=175, mean=100, sd=75)
y <- sort(y)
pct <- 1:length(y)/(length(y)+1)

## For x ticks
probs <- c(0.0001, 0.001, 0.01, 0.1, 0.3, 0.5, 0.7,
           0.9, 0.99, 0.999, 0.9999)
x.vals <- qnorm(probs)     

## Plotting area
xs <- c(-4, 4)
ys <- seq(-2,4)
par(xaxs="i", yaxs="i")
plot(NA, NA, xlim=c(xs[1], xs[2]), ylim=c(min(ys), max(ys)),
     axes=FALSE, xlab=NA, ylab=NA)

## X Axis
axis(side=1, at=x.vals, labels=FALSE, tck=-0.01)

text(x=x.vals, y=rep(min(ys)-0.35, length(x.vals)),
     labels=probs*100, xpd=TRUE, srt=325, font=2)

## Y Axis
axis(side=2, at=ys, labels=FALSE)
text(y=ys, x=rep(xs[1]-.08, length(ys)),
     labels= as.character(10^ys), xpd = NA, font=2,
     pos=2)

for (i in ys){
    axis(side=2, at=log10(seq(2,9))+ i,
         labels=NA, tck = -0.01)
}

## Grid lines and box
abline(h=ys, col="grey80", lty=2)
abline(v=qnorm(probs), col="grey80", lty=2)
box()

## Plot Data
lines(x=qnorm(pct), y=log10(y), col="blue")

enter image description here

joelnNC
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