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: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jacques Wagnor Sent: Sunday, 3 February 2008 12:42 PM To: [EMAIL PROTECTED] 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
