Hello Lib,
I think what you're trying to do is very easy using ggplot2 -- easy, that
is, once you got your hear around ggplot2 in the first place. The layering
you mention is the core feature of ggplot2. Fortunately it is
well-documented including a thin, overpriced book from Springer (which I
have, and like, but am not sure I should recommend).
Good luck,
robert
On Tue, Feb 25, 2014 at 8:34 PM, Lib Gray <libgray3...@gmail.com> wrote:
> Hello,
>
> I am branching out to xyplot for the first time, and I want to layer
> several "complex" xyplots. I have tried using panel functions, but so far I
> lose all complexity from the scatterplot. I would like to have the
> following things in the plot:
>
>
> 1) A plot of observation vs. modeled individual prediction, by treatment
> arm, with each subjects' points connected by lines.
>
>
> xyplot(Observation,IPrediction,groups=TreatmentArm,type="b",col=c(1,2,3),cex=0.7)
>
>
> 2) Over the former, I would like to add loess smoothers.
>
> I am able to do this in the former with "type=c("b","smooth"), but I would
> like to differentiate the smoothers from the rest of the plot with thicker
> line widths, and possibly colors.
>
>
> 3) Also over the former, I would like to add a simple abline(0,1).
>
> I can add this, but not also the loess and treatment arm differences with
> "panel=function(x,y){}, but cannot figure out to keep all the former
> complexity.
>
>
>
> Basically, I am trying to recreated the four basic diagnostic plots from
> "xpose4", but adding color for treatment differences.
>
> Any help would be appreciated!
>
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>
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