Hi,

In my work, I often investigate relationships between highly skewed data.
Example:

set.seed(111)
require(MASS)
d = data.frame(mvrnorm(1000, mu=c(0,0), Sigma=matrix(c(1,.6,.6,1), nrow=2)))
names(d) = c("x","y")
## Skew Y
d$y = d$y^4
plot(d$x, d$y)
lines(lowess(d$x, d$y), lwd=2, col="blue")

Unfortunately, with such skewed data, it's hard to see the line unless we
"zoom in," by either ignoring the outliers, or "breaking" the scale of the
y axis, such that the first 2/3 of the graph correspond to a "normal"
scale, and the remaining 1/3 correspond to a "compressed" scale. (I know
this is generally not recommended, see
http://r.789695.n4.nabble.com/split-a-y-axis-to-show-data-on-different-scales-td805816.html).
I created a function to do this:

scaleBreak = function(x,y,axis=2, breakpos=1,...){

    #### figure out which Y values are above the breakpos
    y_above = y[y>breakpos]; x_above = x[y>breakpos]
    y_below = y[y<=breakpos]; x_below = x[y<=breakpos]

    #### pick ranges
    range_1 = range(y_below)
    range_2 = range(y_above)

    #### find limits of y axis (so it spans 2/3rds)
    mx = max(y_below); mn = min(y_below)
    ylims1 = c(mn, mx + (mx-mn)/2)

    #### plot bottom graph
    plot(range(x), ylims1, type="n", yaxt="n",...)
    points(x_below, y_below, yaxt="n",...)
    axis(2, pretty(y_below))

    min2 = (breakpos + .45*breakpos - max(y))/.45

    #### add second graph
    par(new=TRUE)
    plot(range(x), c(min2, max(y)), type="n", yaxt="n", xaxt="n", ylab="",
axes=F)
    points(x_above, y_above, yaxt="n",...)
    axis(2, pretty(y_above)[-1])
    require(plotrix)
    axis.break(axis=axis, breakpos)

}

The problem I'm having is that the fitted line is not printed on the scale
of the bottom 2/3 plot:

scaleBreak(d$x, d$y, breakpos=20)
lines(lowess(d$x, d$y), lwd=2, col="blue")

Can anyone think of a solution where the line is on the scale of the bottom
2/3 of the plot, in the right location? (Again, let me preempt the
objections others might raise about how this should not be done. I know it
generally should not be done, but let's pretend I have an excellent reason
:) )

Thanks in advance!

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