Thanks a lot - that gives the same result as the idea I had - only much
easier.

Rainer

On Jan 16, 2008 12:18 PM, Dimitris Rizopoulos <
dimitris.rizopoulos@med.kuleuven.be> wrote:

> I think you need:
>
> dx2 <- exp(dx)
> dp2 <- dp / dx2
> sum(c(0, diff(dx2)) * dp2)
>
>
> I hope it helps.
>
> Best,
> Dimitris
>
> ----
> Dimitris Rizopoulos
> Ph.D. Student
> Biostatistical Centre
> School of Public Health
> Catholic University of Leuven
>
> Address: Kapucijnenvoer 35, Leuven, Belgium
> Tel: +32/(0)16/336899
> Fax: +32/(0)16/337015
> Web: http://med.kuleuven.be/biostat/
>     http://www.student.kuleuven.be/~m0390867/dimitris.htm<http://www.student.kuleuven.be/%7Em0390867/dimitris.htm>
>
>
>
> ----- Original Message -----
> From: "Rainer M Krug" <R.M.Krug@gmail.com>
> To: "r-help" <r-help@stat.math.ethz.ch>
> Sent: Wednesday, January 16, 2008 10:34 AM
> Subject: [R] Question concerning pdfs
>
>
> > Hi
> >
> > I have a dataset of absolute growth rates g ranging from close to 0
> > to
> > around whatever of which I want to calculate a pdf.
> > If I use density(g) the pdf will extend to below 0 so I logtransform
> > g
> > and do d <- density(log(g)).
> > Now I would like to transform this pdf back, i.e. d$x <-
> > exp(d$x) but what do I have to do with d$y?
> >
> > (below is a small example)
> >
> > Thanks for your help,
> >
> > Rainer
> >
> >
> > g <- exp(rnorm(100)) ## Just to generate the example data
> >
> > d <- density(log(g))
> > dx <- d$x
> > dp <- d$y
> >
> > sum(c(0, (diff(dx))) * dp) ## this is equal to one
> > plot(dx, dp)
> >
> > dx2 <- exp(dx)
> > dp2 <- ???????          ## what should I do here?
> >
> > plot(dx2, dp2)          ## what should I do here?
> > sum(c(0, (diff(exp(dx2)))) * dp2)    ## this should be one
> >
> >
> > sum( c(0, (diff(dx2))) * ( dp1 / c(1, (diff(exp(dx2)))) * c(0,
> > (diff(dx1)))) )               ##This is obviously also one, but can
> > I
> > use this to define my dp2? i.e.
> >
> > dp2 <- dp1 / c(1, (diff(exp(dx2)))) * c(0, (diff(dx1)))) ###????
> >
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> >
>
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