This is an interesting exercise. I see at as an application of
a Likert plot. I would start with this
tmp <- data.frame(x = c(0.1,0.6,0.2,0.1),
y = c(0.5,0.2,0.2,0.1))
tmp$xx <- 1
tmp$yy <- tmp$x / tmp$y
tmp$xy <- tmp$xx * tmp$x
tmp$xxx <- tmp$xx - tmp$xy
tmp$yyy <- tmp$yy - tmp$xy
tmp
## install.packages(HH) ## if necessaruy
require(HH)
likert(tmp[, c("xxx","xy","yyy")],
xlab="scaled to xxx+xy = 1",
sub="xxx+xy = 1, xy/(xxx+xy) = x, xy/(xy+yyy) = y")
My guess is that this graph would be more meaningful if it were scaled to
counts rather than to xxx + xy = 1.
Rich
On Tue, Nov 13, 2012 at 7:05 AM, Stefan Sobernig
<stefan.sober...@wu.ac.at>wrote:
> I am looking at a data set containing two variables (x,y), each of which
> represents relative frequencies (rounded):
>
> data.frame(x = c(0.1,0.6,0.2,0.1), y = c(0.5,0.2,0.2,0.1))
>
> x y
> 1 0.1 0.5
> 2 0.6 0.2
> 3 0.2 0.2
> 4 0.1 0.1
>
> each of the rows reflects a "relation" between x and y, for example in row
> 4: 10% of the observations in x account for 10% of the observations in y.
>
> I feel embarrassed, but my mind went blank, and I can't think of a proper
> way of visualizing this "relation" based on the data above (nor of the
> appropriate terminology to phrase my question other than "by example").
>
> My apologies and thanks for your hints!
>
> //stefan
>
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