[R] Confidence Interval

[Jacques Wagnor]

The motivation for the question comes from Figure 3 of this paper
http://www.ma.hw.ac.uk/~mcneil/ftp/cad.pdf, which shows that a
confidence interval for a statistic is possible.  Does there exist a
function in R for such a calculation?  If not, how would one go about
doing it in R?

Any pointers would be greatly appreciated.

On Feb 3, 2008 12:21 AM,  <Bill.Venables at csiro.au> wrote:
> Your question is not clear.  Confidence intervals apply to parameters.
> What you set out below is a simulation strategy.  x is a simulated
> sample and y is a statistic based on it.  There is no 'model' in any
> statistical sense.
>
> What is the parameter for which you want a confidence interval?
>
> What data set, or sets, will you have available to do it?
>
> Do you want to make parametric assumptions (in which case the Likelihood
> Ratio interval may be possible) or do you want to use a non-parametric
> interval, keeping the assumptions as weak as possible (in which case,
> inverting the sign test might be appropriate)?
>
> Finally, what has this got to do with R-help?
>
>
>
>
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On Behalf Of Jacques Wagnor
> Sent: Sunday, 3 February 2008 12:42 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Confidence Interval
>
> I have a model as follows:
>
> x <- replicate(100, sum(rlnorm(rpois(1,5), 0,1)))
> y <- quantile(x, 0.99)
>
> How would one go about estimating the boundaries of a 95% confidence
> interval for y?
>
> Any pointers would be greatly appreciated.
>
> > version
> _
> platform i386-pc-mingw32
> arch i386
> os mingw32
> system i386, mingw32
> status
> major 2
> minor 5.1
> year 2007
> month 06
> day 27
> svn rev 42083
> language R
> version.string R version 2.5.1 (2007-06-27)
>
> Jacques
>
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>
>
>