[R] Confidence Interval

[Bill.Venables at csiro.au]

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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