On Wed, Oct 7, 2009 at 1:48 PM, Petr PIKAL <petr.pikal@precheza.cz> wrote:

> Hi
>
> Rainer M Krug <r.m.krug@gmail.com> napsal dne 07.10.2009 12:40:39:
>
> >
>
> > On Wed, Oct 7, 2009 at 12:26 PM, Petr PIKAL <petr.pikal@precheza.cz>
> wrote:
> > Hi
> >
> > Rainer M Krug <r.m.krug@gmail.com> napsal dne 07.10.2009 12:09:21:
> >
> > >
> >
>
> <snip>
>
> > In the meantime, what about
> >
> > x <- rnorm(200)
> > hist(x, col = "blue", freq = TRUE)
> > ddd<-density(x)
> > lines(ddd$x, ddd$y*100, col = "red", lwd = 2)
> >
> > and then add suitable y axis.
> >
> > axis(4, at=pretty(ddd$y*100), labels=pretty(ddd$y), col=2)
> >
> > Yes - that definitely works.
> >
> > I usually use the following approach: determine the xlims in advance,
> and then
> > set them manually for each plot:
> >
> > x <- rnorm(200)
> > xlim <- trunc(range(x)) + c(-1, +1)
> >
> > hist(x, col = "blue", freq = TRUE, xlim=xlim)
>
> hhh <- hist(x, col = "blue", freq = TRUE)
>
> gives you object from which you can extract limits for plotting maybe
> better then from original data and you do not need to call
>
> > par(new=TRUE)
>
> True.

Thanks a lot,

Rainer


> Regards
> Petr
>
> > plot(density(x), xlim=xlim, ann=FALSE, axes=FALSE)
> > axis(4)
> >
> > But it is sometimes tricky to get the xlims for the plot.
> >
> > Regards
> > Petr
> >
>
>


-- 
Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology,
UCT), Dipl. Phys. (Germany)

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